Starting Dynare (version 6.4).
Calling Dynare with arguments: none
Starting preprocessing of the model file ... 
Found 16 equation(s). 
Evaluating expressions... 
Computing static model derivatives (order 1). 
Normalizing the static model... 
Finding the optimal block decomposition of the static model... 
7 block(s) found: 
  5 recursive block(s) and 2 simultaneous block(s). 
  the largest simultaneous block has 9 equation(s) 
                                 and 9 feedback variable(s). 
Computing dynamic model derivatives (order 2). 
Normalizing the dynamic model... 
Finding the optimal block decomposition of the dynamic model... 
3 block(s) found: 
  1 recursive block(s) and 2 simultaneous block(s). 
  the largest simultaneous block has 9 equation(s) 
                                 and 7 feedback variable(s). 
Preprocessing completed. 
Preprocessing time: 0h00m00s.
Initial value of the log posterior (or likelihood): -21270.8513
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.925177e-23.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 97)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',97,0)">line 97</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Gradient norm  4006190.2209
Minimum Hessian eigenvalue -6.499e-10
Maximum Hessian eigenvalue 299093690219.2739
 
Iteration 1
Correct for low angle: 4.86663e-13
Predicted improvement: 752499526234092.750000000
lambda =          1; f = 2315030342656722.0000000
lambda =    0.33333; f = 257225589416496.8750000
lambda =    0.11111; f = 28580619654879.9687500
lambda =   0.037037; f = 3175623954910.4023438
lambda =   0.012346; f = 352846968317.1457520
lambda =  0.0041152; f =  39205185385.6826553
lambda =  0.0013717; f =   4356133215.8936672
lambda = 0.00045725; f =    484027915.6712761
lambda = 0.00015242; f =     53797862.6016567
lambda = 5.0805e-05; f =      5995813.0974701
lambda = 1.6935e-05; f =       684904.1722619
lambda =  5.645e-06; f =        94946.4834356
lambda = 1.8817e-06; f =        29439.5561710
lambda = 6.2723e-07; f =        22173.3583278
lambda = 2.0908e-07; f =        21369.7589337
lambda = 6.9692e-08; f =        21281.4067853
lambda = 2.3231e-08; f =        21271.8901887
lambda = 7.7435e-09; f =        21270.9328919
lambda = 2.5812e-09; f =        21270.8553684

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =   2220613124.8401289
lambda = -2.0908e-07; f =    246687088.5838903
lambda = -6.9692e-08; f =     27406386.4318052
lambda = -2.3231e-08; f =      3056668.2996281
lambda = -7.7435e-09; f =       356078.8391080
lambda = -2.5812e-09; f =        57658.2689576
Norm of dx 7.5135e+10
Predicted improvement: 8024780042832.179687500
lambda =          1; f = 263275363096.2270203
lambda =    0.33333; f =  29252791920.1437378
lambda =    0.11111; f =   3250314091.2437434
lambda =   0.037037; f =    361159914.5505286
lambda =   0.012346; f =     40146125.9794699
lambda =  0.0041152; f =      4479041.3068962
lambda =  0.0013717; f =       516403.2513471
lambda = 0.00045725; f =        76233.9182354
lambda = 0.00015242; f =        27362.9336874
lambda = 5.0805e-05; f =        21943.4465883
lambda = 1.6935e-05; f =        21344.4169848
lambda =  5.645e-06; f =        21278.6523674
lambda = 1.8817e-06; f =        21271.6045936
lambda = 6.2723e-07; f =        21270.9079763
lambda = 2.0908e-07; f =        21270.8537070
lambda = 6.9692e-08; f =        21270.8512911
lambda = 2.3231e-08; f =          224.6776043
lambda = 7.7435e-09; f =         1861.7138655
lambda = 2.5812e-09; f =         5882.9064347
Norm of dx 4.0062e+06
Gradient step!!
Predicted improvement:       42.651709668
lambda =          1; f =          150.5780381
lambda =     1.9332; f =           97.5727004
lambda =     3.7372; f =           24.5079888
Norm of dx  0.0015815
Done for param e_a =   0.0227; f =  24.5080
Predicted improvement:       31.775805091
lambda =          1; f =          -16.3528375
Norm of dx   0.028654
Done for param e_v =   0.1306; f = -16.3528
Predicted improvement:       47.107598267
lambda =          1; f =          -89.7177399
lambda =     1.9332; f =         -132.4831796
Norm of dx  0.0021383
Done for param e_g =   0.0168; f = -132.4832
Predicted improvement:       96.601934877
lambda =          1; f =         -256.9244655
Norm of dx  0.0041224
Done for param e_rer =   0.0170; f = -256.9245
Predicted improvement:        0.003415057
lambda =          1; f =         -256.9279213
Norm of dx 7.2834e-05
Done for param e_yw =   0.0101; f = -256.9279
Predicted improvement:        0.008044041
lambda =          1; f =         -256.9440079
lambda =     1.9332; f =         -256.9590169
lambda =     3.7372; f =         -256.9880247
lambda =     7.2247; f =         -257.0440744
lambda =     13.967; f =         -257.1523256
lambda =         27; f =         -257.3612101
lambda =     52.196; f =         -257.7635865
lambda =      100.9; f =         -258.5361071
lambda =     195.07; f =         -260.0096798
lambda =      377.1; f =         -262.7851072
lambda =        729; f =         -267.8832567
lambda =     1409.3; f =         -276.7848263
lambda =     2724.4; f =         -290.7198250
lambda =     5266.8; f =         -307.1638180
Norm of dx 6.7564e-06
Done for param alp =   0.2887; f = -307.1638
Predicted improvement:        0.018001640
lambda =          1; f =         -307.1998032
lambda =     1.9332; f =         -307.2333511
lambda =     3.7372; f =         -307.2981156
lambda =     7.2247; f =         -307.4229828
lambda =     13.967; f =         -307.6631265
lambda =         27; f =         -308.1227294
lambda =     52.196; f =         -308.9940493
lambda =      100.9; f =         -310.6154060
lambda =     195.07; f =         -313.5219241
lambda =      377.1; f =         -318.3414468
lambda =        729; f =         -324.9958651
Norm of dx 1.6968e-05
Done for param bet =   0.9226; f = -324.9959
Predicted improvement:        0.061965348
lambda =          1; f =         -325.1179796
lambda =     1.9332; f =         -325.2286586
lambda =     3.7372; f =         -325.4336541
lambda =     7.2247; f =         -325.7964370
lambda =     13.967; f =         -326.3725316
lambda =         27; f =         -327.0182641
Norm of dx  6.028e-05
Done for param delt =   0.0987; f = -327.0183
Predicted improvement:        0.003748347
lambda =          1; f =         -327.0257591
lambda =     1.9332; f =         -327.0327503
lambda =     3.7372; f =         -327.0462572
lambda =     7.2247; f =         -327.0723374
lambda =     13.967; f =         -327.1226392
lambda =         27; f =         -327.2194471
lambda =     52.196; f =         -327.4049675
lambda =      100.9; f =         -327.7575080
lambda =     195.07; f =         -328.4160475
lambda =      377.1; f =         -329.6019188
lambda =        729; f =         -331.5583123
lambda =     1409.3; f =         -333.9972657
Norm of dx 8.6126e-05
Done for param sig =   1.8784; f = -333.9973
Predicted improvement:        0.001425376
lambda =          1; f =         -334.0001159
lambda =     1.9332; f =         -334.0027748
lambda =     3.7372; f =         -334.0079124
lambda =     7.2247; f =         -334.0178350
lambda =     13.967; f =         -334.0369825
lambda =         27; f =         -334.0738680
lambda =     52.196; f =         -334.1446893
lambda =      100.9; f =         -334.2797880
lambda =     195.07; f =         -334.5342030
lambda =      377.1; f =         -335.0008924
lambda =        729; f =         -335.8098553
lambda =     1409.3; f =         -337.0300560
lambda =     2724.4; f =         -338.1322424
Norm of dx 5.0386e-05
Done for param phi1 =   1.6375; f = -338.1322
Predicted improvement:        0.000763427
lambda =          1; f =         -338.1337692
lambda =     1.9332; f =         -338.1351939
lambda =     3.7372; f =         -338.1379481
lambda =     7.2247; f =         -338.1432719
lambda =     13.967; f =         -338.1535621
lambda =         27; f =         -338.1734484
lambda =     52.196; f =         -338.2118677
lambda =      100.9; f =         -338.2860479
lambda =     195.07; f =         -338.4291103
lambda =      377.1; f =         -338.7043993
lambda =        729; f =         -339.2318093
lambda =     1409.3; f =         -340.2335240
lambda =     2724.4; f =         -342.1030826
lambda =     5266.8; f =         -345.4658057
lambda =      10182; f =         -351.0164425
lambda =      19683; f =         -358.1076031
Norm of dx 7.3895e-05
Done for param phi2 =   4.1454; f = -358.1076
Predicted improvement:        0.066339069
lambda =          1; f =         -358.2397350
lambda =     1.9332; f =         -358.3620545
lambda =     3.7372; f =         -358.5958359
lambda =     7.2247; f =         -359.0377948
lambda =     13.967; f =         -359.8552215
lambda =         27; f =         -361.2997230
lambda =     52.196; f =         -363.6006306
lambda =      100.9; f =         -366.3029193
Norm of dx  0.0004508
Done for param hf =   0.4547; f = -366.3029
Predicted improvement: 550185177681.944213867
lambda =          1; f = 1100370355317499756544.0000000
lambda =    0.33333; f = 122263372802747023360.0000000
lambda =    0.11111; f = 13584819196869058560.0000000
lambda =   0.037037; f = 1509424354062297600.0000000
lambda =   0.012346; f = 167713816736253952.0000000
lambda =  0.0041152; f = 18634868399003332.0000000
lambda =  0.0013717; f = 2070540890819496.7500000
lambda = 0.00045725; f = 230060084858184.0625000
lambda = 0.00015242; f = 25562226956261.2304688
lambda = 5.0805e-05; f = 2840245887307.1176758
lambda = 1.6935e-05; f = 315582371546.8746338
lambda =  5.645e-06; f =  35064552281.3637619
lambda = 1.8817e-06; f =   3896022080.4049392
lambda = 6.2723e-07; f =    432890852.7755000
lambda = 2.0908e-07; f =     48111425.7164462
lambda = 6.9692e-08; f =      5362466.5653646
lambda = 2.3231e-08; f =       614019.0559599
lambda = 7.7435e-09; f =        86892.7240423
lambda = 2.5812e-09; f =        28482.7805754

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =    432907447.5185293
lambda = -2.0908e-07; f =     48116957.0316868
lambda = -6.9692e-08; f =      5364310.0713423
lambda = -2.3231e-08; f =       614633.2921833
lambda = -7.7435e-09; f =        87097.2036810
lambda = -2.5812e-09; f =        28550.6746859
Norm of dx 3.3172e+10
Done for param rhoa =   0.6996; f = -366.3029
Predicted improvement:        0.000117326
lambda =          1; f =         -366.3031539
lambda =     1.9332; f =         -366.3033727
lambda =     3.7372; f =         -366.3037954
lambda =     7.2247; f =         -366.3046114
lambda =     13.967; f =         -366.3061849
lambda =         27; f =         -366.3092111
lambda =     52.196; f =         -366.3150033
lambda =      100.9; f =         -366.3259824
lambda =     195.07; f =         -366.3463832
lambda =      377.1; f =         -366.3826817
lambda =        729; f =         -366.4406563
lambda =     1409.3; f =         -366.5034651
Norm of dx   2.81e-05
Done for param rhov =   0.5392; f = -366.5035
Predicted improvement:        0.633882550
lambda =          1; f =         -367.7085787
lambda =     1.9332; f =         -368.7200285
lambda =     3.7372; f =         -370.3649029
lambda =     7.2247; f =         -372.3779238
Norm of dx   0.017004
Done for param rhog =   0.6228; f = -372.3779
Predicted improvement:       19.775179322
lambda =          1; f =         -408.3845787
lambda =     1.9332; f =         -435.5963839
lambda =     3.7372; f =         -470.7535566
Norm of dx    0.14977
Done for param rhorer =   0.5597; f = -470.7536
Predicted improvement:        0.000089833
lambda =          1; f =         -470.7536459
Norm of dx  0.0010014
Done for param rhoyw =   0.5510; f = -470.7536
Sequence of univariate steps!!
Actual dxnorm 1.5807
FVAL          -470.7536
Improvement   21741.6049
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.425699e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.75298 s.
 
Iteration 2
Correct for low angle: 1.2484e-14
Predicted improvement: 12707579814873.449218750
lambda =          1; f = 114688921084754533548032.0000000
lambda =    0.33333; f = 12743213453382879543296.0000000
lambda =    0.11111; f = 1415912605771849269248.0000000
lambda =   0.037037; f = 157323622810345242624.0000000
lambda =   0.012346; f = 17480402516751593472.0000000
lambda =  0.0041152; f = 1942266940395328768.0000000
lambda =  0.0013717; f = 215807435851568544.0000000
lambda = 0.00045725; f = 23978603326795776.0000000
lambda = 0.00015242; f = 2664289039628648.5000000
lambda = 5.0805e-05; f = 296032042545952.0000000
lambda = 1.6935e-05; f = 32892424848721.4179688
lambda =  5.645e-06; f = 3654705764126.2255859
lambda = 1.8817e-06; f = 406075715314.0104370
lambda = 6.2723e-07; f =  45118622677.5595474
lambda = 2.0908e-07; f =   5012879609.9052849
lambda = 6.9692e-08; f =    556886121.6371788
lambda = 2.3231e-08; f =     61842462.2840560
lambda = 7.7435e-09; f =      6859853.9109229
lambda = 2.5812e-09; f =       758089.4242710

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1127365.8121967
lambda = -2.0908e-07; f =       124822.3187493
lambda = -6.9692e-08; f =        13444.2042364
lambda = -2.3231e-08; f =         1073.3012325
lambda = -7.7435e-09; f =         -299.8671682
lambda = -2.5812e-09; f =         -451.9860623
Norm of dx 3.3866e+11
Predicted improvement: 112640407.400998041
lambda =          1; f =        10116.3551356
lambda =    0.33333; f =          658.6238755
lambda =    0.11111; f =         -359.8364650
lambda =   0.037037; f =         -462.5091476
lambda =   0.012346; f =         -470.5460091
lambda =  0.0041152; f =         -403.6743940
lambda =  0.0013717; f =         -463.8724667
lambda = 0.00045725; f =         -470.1601978
lambda = 0.00015242; f =         -470.7251867
lambda = 5.0805e-05; f =         -470.7533232
lambda = 1.6935e-05; f =         -470.7536455
lambda =  5.645e-06; f =         -574.3159847
lambda = 1.8817e-06; f =         -600.5091776
Norm of dx      15009
Gradient step!!
Predicted improvement:       29.848154783
lambda =          1; f =         -638.4824770
Norm of dx    0.22249
Predicted improvement:        0.918284883
lambda =          1; f =         -640.0259184
lambda =     1.9332; f =         -641.0094732
lambda =     3.7372; f =         -641.9625051
Norm of dx  0.0023471
Done for param e_a =   0.0537; f = -641.9625
Predicted improvement:        0.055745074
lambda =          1; f =         -642.0207477
Norm of dx  0.0037127
Done for param e_v =   0.1343; f = -642.0207
Predicted improvement:        0.073174942
lambda =          1; f =         -642.1436278
lambda =     1.9332; f =         -642.2128646
Norm of dx 0.00075364
Done for param e_g =   0.0348; f = -642.2129
Predicted improvement:        0.178563677
lambda =          1; f =         -642.3901325
Norm of dx  0.0011562
Done for param e_rer =   0.0236; f = -642.3901
Predicted improvement:        0.085225424
lambda =          1; f =         -642.4693967
Norm of dx 0.00040617
Done for param e_yw =   0.0100; f = -642.4694
Predicted improvement:       31.339888212
lambda =          1; f =         -628.5122454
lambda =    0.33333; f =         -656.6912809
Norm of dx   0.077776
Done for param alp =   0.3396; f = -656.6913
Predicted improvement:        1.263693657
lambda =          1; f =         -658.0044415
Norm of dx  0.0063442
Done for param bet =   0.9267; f = -658.0044
Predicted improvement:        0.070037554
lambda =          1; f =         -658.0743814
Norm of dx 0.00037425
Done for param delt =   0.0996; f = -658.0744
Predicted improvement:        1.244746610
lambda =          1; f =         -659.4728753
Norm of dx   0.086263
Done for param sig =   2.0792; f = -659.4729
Predicted improvement:        2.434223408
lambda =          1; f =         -661.5064476
Norm of dx    0.16653
Done for param phi1 =   1.5791; f = -661.5064
Predicted improvement:        1.013443989
lambda =          1; f =         -662.5101401
Norm of dx    0.40544
Done for param phi2 =   3.6962; f = -662.5101
Predicted improvement:        0.434089694
lambda =          1; f =         -662.9649232
Norm of dx   0.018808
Done for param hf =   0.4958; f = -662.9649
Predicted improvement:        1.671566360
lambda =          1; f =         -664.8088779
Norm of dx    0.11508
Done for param rhoa =   0.5389; f = -664.8089
Predicted improvement:        0.083574271
lambda =          1; f =         -664.8961639
Norm of dx   0.030282
Done for param rhov =   0.3932; f = -664.8962
Predicted improvement:        0.040564538
lambda =          1; f =         -664.9367996
Norm of dx   0.022094
Done for param rhog =   0.5920; f = -664.9368
Predicted improvement:        1.896353971
lambda =          1; f =         -666.2223850
Norm of dx    0.15841
Done for param rhorer =   0.7587; f = -666.2224
Predicted improvement:        0.115328514
lambda =          1; f =         -666.3388163
Norm of dx   0.035183
Done for param rhoyw =   0.5541; f = -666.3388
Sequence of univariate steps!!
Actual dxnorm 0.58206
FVAL          -666.3388
Improvement   195.5852
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  6.636085e-23.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.30204 s.
 
Iteration 3
Near-singular H problem.
Correct for low angle: 9.28666e-24
Predicted improvement: 9553984514162.691406250
lambda =          1; f = 13121133881018208256.0000000
lambda =    0.33333; f = 1457903764283120128.0000000
lambda =    0.11111; f = 161989307051082400.0000000
lambda =   0.037037; f = 17998811864068810.0000000
lambda =   0.012346; f = 1999867974730841.7500000
lambda =  0.0041152; f = 222207549358915.5625000
lambda =  0.0013717; f = 24689726576502.5937500
lambda = 0.00045725; f = 2743302575871.8852539
lambda = 0.00015242; f = 304811271236.4920654
lambda = 5.0805e-05; f =  33867876607.0845184
lambda = 1.6935e-05; f =   3763082869.3994284
lambda =  5.645e-06; f =    418115083.3692985
lambda = 1.8817e-06; f =     46455094.6775779
lambda = 6.2723e-07; f =      5160573.2508827
lambda = 2.0908e-07; f =       572637.1490106
lambda = 6.9692e-08; f =        62980.9748612
lambda = 2.3231e-08; f =         6390.1440695
lambda = 7.7435e-09; f =          113.2905684
lambda = 2.5812e-09; f =         -580.9644368

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     47782305.7287757
lambda = -2.0908e-07; f =      5308408.2431327
lambda = -6.9692e-08; f =       589183.5319700
lambda = -2.3231e-08; f =        64856.8729542
lambda = -7.7435e-09; f =         6608.8102923
lambda = -2.5812e-09; f =          140.2883320
Norm of dx 1.1601e+10
Predicted improvement:  1356488.971101786
lambda =          1; f =       263668.9603675
lambda =    0.33333; f =        28669.4384078
lambda =    0.11111; f =         2583.2495628
lambda =   0.037037; f =         -308.1143370
lambda =   0.012346; f =         -627.3202703
lambda =  0.0041152; f =         -662.2357334
lambda =  0.0013717; f =         -665.9488346
lambda = 0.00045725; f =         -666.3065696
lambda = 0.00015242; f =         -666.3370495
lambda = 5.0805e-05; f =         -666.3388143
lambda = 1.6935e-05; f =         -647.1048603
lambda =  5.645e-06; f =         -669.2743584
lambda = 1.8817e-06; f =         -669.6615888
Norm of dx     1647.1
Gradient step!!
Predicted improvement:       25.593377551
lambda =          1; f =         -643.0548776
lambda =    0.33333; f =         -665.3535792
lambda =    0.11111; f =         -640.8923104
lambda =   0.037037; f =         -668.0424982
lambda =   0.012346; f =         -669.9988595
Norm of dx     6.1458
Predicted improvement:        0.367555602
lambda =          1; f =         -670.4026387
Norm of dx  0.0036724
Done for param e_a =   0.0576; f = -670.4026
Predicted improvement:        0.258470433
lambda =          1; f =         -670.6833741
Norm of dx  0.0076964
Done for param e_v =   0.1400; f = -670.6834
Predicted improvement:        0.447474423
lambda =          1; f =         -671.1813825
Norm of dx  0.0026342
Done for param e_g =   0.0382; f = -671.1814
Predicted improvement:        0.487709413
lambda =          1; f =         -671.7212866
Norm of dx  0.0020502
Done for param e_rer =   0.0286; f = -671.7213
Predicted improvement:        0.000718363
lambda =          1; f =         -671.7220008
Norm of dx 3.4312e-05
Done for param e_yw =   0.0101; f = -671.7220
Predicted improvement:        0.222888550
lambda =          1; f =         -671.9374991
Norm of dx  0.0044079
Done for param alp =   0.3450; f = -671.9375
Predicted improvement:        0.000284071
lambda =          1; f =         -671.9377815
Norm of dx 9.3385e-05
Done for param bet =   0.9240; f = -671.9378
Predicted improvement:        0.142298692
lambda =          1; f =         -672.0800802
Norm of dx 0.00053284
Done for param delt =   0.0997; f = -672.0801
Predicted improvement:        0.268902772
lambda =          1; f =         -672.3516366
Norm of dx   0.045498
Done for param sig =   2.1163; f = -672.3516
Predicted improvement:        0.156088578
lambda =          1; f =         -672.5052955
Norm of dx   0.039553
Done for param phi1 =   1.4763; f = -672.5053
Predicted improvement:        0.317627843
lambda =          1; f =         -672.8251119
Norm of dx    0.22538
Done for param phi2 =   3.8817; f = -672.8251
Predicted improvement:        0.029398716
lambda =          1; f =         -672.8540237
Norm of dx  0.0054372
Done for param hf =   0.4943; f = -672.8540
Predicted improvement:        0.285364545
lambda =          1; f =         -673.1442383
Norm of dx   0.053536
Done for param rhoa =   0.4895; f = -673.1442
Predicted improvement:        0.003863998
lambda =          1; f =         -673.1481393
Norm of dx  0.0068381
Done for param rhov =   0.3899; f = -673.1481
Predicted improvement:        0.001698599
lambda =          1; f =         -673.1498401
Norm of dx  0.0048173
Done for param rhog =   0.5887; f = -673.1498
Predicted improvement:        0.421245838
lambda =          1; f =         -673.5723291
Norm of dx   0.075301
Done for param rhorer =   0.6843; f = -673.5723
Sequence of univariate steps!!
Actual dxnorm 0.23333
FVAL          -673.5723
Improvement   7.2335
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  6.212916e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.28825 s.
 
Iteration 4
Correct for low angle: 1.07339e-13
Predicted improvement: 1443412518339.977294922
lambda =          1; f = 762515766848844311035904.0000000
lambda =    0.33333; f = 84723974093081484984320.0000000
lambda =    0.11111; f = 9413774898819781099520.0000000
lambda =   0.037037; f = 1045974988620586156032.0000000
lambda =   0.012346; f = 116219443134342873088.0000000
lambda =  0.0041152; f = 12913271444130662400.0000000
lambda =  0.0013717; f = 1434807933156485120.0000000
lambda = 0.00045725; f = 159423101990635200.0000000
lambda = 0.00015242; f = 17713677434486160.0000000
lambda = 5.0805e-05; f = 1968186193451413.5000000
lambda = 1.6935e-05; f = 218687292108157.0625000
lambda =  5.645e-06; f = 24298567105033.8593750
lambda = 1.8817e-06; f = 2699833820061.5693359
lambda = 6.2723e-07; f = 299979212040.8491821
lambda = 2.0908e-07; f =  33330248660.2426453
lambda = 6.9692e-08; f =   3703102269.5839362
lambda = 2.3231e-08; f =    411369184.0363115
lambda = 7.7435e-09; f =     45678419.5233141
lambda = 2.5812e-09; f =      5065230.9369962

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      6023225.0341097
lambda = -2.0908e-07; f =       668566.3089246
lambda = -6.9692e-08; f =        73659.5102366
lambda = -2.3231e-08; f =         7576.9011860
lambda = -7.7435e-09; f =          240.3290743
lambda = -2.5812e-09; f =         -572.9497914
Norm of dx 8.7323e+11
Predicted improvement:   218586.949636926
lambda =          1; f =        85262.6941955
lambda =    0.33333; f =         8861.7123894
lambda =    0.11111; f =          381.8395643
lambda =   0.037037; f =         -557.5998349
lambda =   0.012346; f =         -661.1059715
lambda =  0.0041152; f =         -672.3146471
lambda =  0.0013717; f =         -673.4627201
lambda = 0.00045725; f =         -673.5637171
lambda = 0.00015242; f =         -673.5721059
lambda = 5.0805e-05; f =         -643.2884535
lambda = 1.6935e-05; f =         -671.1045930
lambda =  5.645e-06; f =         -674.6362624
Norm of dx     661.19
Gradient step!!
Predicted improvement:       27.690996353
lambda =          1; f =         -514.8708581
lambda =    0.33333; f =         -661.4191512
lambda =    0.11111; f =         -673.0321300
lambda =   0.037037; f =         -658.3536319
lambda =   0.012346; f =         -673.3215153
lambda =  0.0041152; f =         -674.6508305
lambda =  0.0013717; f =         -674.6914198
lambda =  0.0026518; f =         -674.6975174
Norm of dx      13.89
Predicted improvement:        0.181573508
lambda =          1; f =         -674.8923900
Norm of dx  0.0029116
Done for param e_a =   0.0618; f = -674.8924
Predicted improvement:        0.239181419
lambda =          1; f =         -675.1518432
Norm of dx   0.007833
Done for param e_v =   0.1474; f = -675.1518
Predicted improvement:        0.007931993
lambda =          1; f =         -675.1599138
Norm of dx 0.00043099
Done for param e_g =   0.0395; f = -675.1599
Predicted improvement:        0.017849095
lambda =          1; f =         -675.1772291
Norm of dx 0.00054607
Done for param e_rer =   0.0311; f = -675.1772
Predicted improvement:        0.101766513
lambda =          1; f =         -675.2777382
Norm of dx  0.0030814
Done for param alp =   0.3475; f = -675.2777
Predicted improvement:        0.002080489
lambda =          1; f =         -675.2798321
Norm of dx 0.00026333
Done for param bet =   0.9220; f = -675.2798
Predicted improvement:        0.019781486
lambda =          1; f =         -675.2996134
Norm of dx 0.00019867
Done for param delt =   0.0998; f = -675.2996
Predicted improvement:        0.138253877
lambda =          1; f =         -675.4387430
Norm of dx   0.033675
Done for param sig =   2.1405; f = -675.4387
Predicted improvement:        0.020426219
lambda =          1; f =         -675.4590535
Norm of dx   0.014375
Done for param phi1 =   1.4298; f = -675.4591
Predicted improvement:        0.276804863
lambda =          1; f =         -675.7377723
Norm of dx     0.2172
Done for param phi2 =   4.0837; f = -675.7378
Predicted improvement:        0.266602232
lambda =          1; f =         -675.9896393
Norm of dx   0.016774
Done for param hf =   0.5100; f = -675.9896
Predicted improvement:        0.014110420
lambda =          1; f =         -676.0037812
Norm of dx     0.0122
Done for param rhoa =   0.4774; f = -676.0038
Predicted improvement:        0.000031084
lambda =          1; f =         -676.0038123
Norm of dx 0.00062111
Done for param rhov =   0.3899; f = -676.0038
Predicted improvement:        0.001985108
lambda =          1; f =         -676.0057947
Norm of dx  0.0053015
Done for param rhog =   0.5944; f = -676.0058
Predicted improvement:        0.067676116
lambda =          1; f =         -676.0735424
Norm of dx   0.031821
Done for param rhorer =   0.6526; f = -676.0735
Sequence of univariate steps!!
Actual dxnorm 0.21231
FVAL          -676.0735
Improvement   2.5012
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.716529e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.28493 s.
 
Iteration 5
Correct for low angle: 1.45831e-13
Predicted improvement: 1079746939402.525024414
lambda =          1; f = 585287641746335967739904.0000000
lambda =    0.33333; f = 65031960192955740848128.0000000
lambda =    0.11111; f = 7225773354412327043072.0000000
lambda =   0.037037; f = 802863705925636849664.0000000
lambda =   0.012346; f = 89207078396122808320.0000000
lambda =  0.0041152; f = 9911897586216177664.0000000
lambda =  0.0013717; f = 1101321949573012864.0000000
lambda = 0.00045725; f = 122369104024442992.0000000
lambda = 0.00015242; f = 13596566619270094.0000000
lambda = 5.0805e-05; f = 1510729459510650.0000000
lambda = 1.6935e-05; f = 167858773883225.2812500
lambda =  5.645e-06; f = 18650956558422.7773438
lambda = 1.8817e-06; f = 2072322400266.9550781
lambda = 6.2723e-07; f = 230256008671.7110291
lambda = 2.0908e-07; f =  25583321968.4541779
lambda = 6.9692e-08; f =   2842364603.8675370
lambda = 2.3231e-08; f =    315742319.7274377
lambda = 7.7435e-09; f =     35056762.4300938
lambda = 2.5812e-09; f =      3886228.7048276

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      3869428.4613019
lambda = -2.0908e-07; f =       429260.3469065
lambda = -6.9692e-08; f =        47069.7810756
lambda = -2.3231e-08; f =         4620.9412394
lambda = -7.7435e-09; f =          -90.0346482
lambda = -2.5812e-09; f =         -611.7677534
Norm of dx 7.6505e+11
Predicted improvement:   159355.902188346
lambda =          1; f =       103669.2004431
lambda =    0.33333; f =        10901.6997512
lambda =    0.11111; f =          605.3338694
lambda =   0.037037; f =         -535.1695456
lambda =   0.012346; f =         -660.8929916
lambda =  0.0041152; f =         -674.5325746
lambda =  0.0013717; f =         -675.9381875
lambda = 0.00045725; f =         -676.0625655
lambda = 0.00015242; f =         -676.0731336
lambda = 5.0805e-05; f =         -652.4563357
lambda = 1.6935e-05; f =         -674.6563251
lambda =  5.645e-06; f =         -676.9569431
Norm of dx     564.55
Correct for low angle: 0.0046224
Predicted improvement:       28.339458773
lambda =          1; f =         -318.4973304
lambda =    0.33333; f =         -643.8916283
lambda =    0.11111; f =         -673.8668164
lambda =   0.037037; f =         -676.0596756
lambda =   0.012346; f =         -663.3986681
lambda =  0.0041152; f =         -675.7065883
lambda =  0.0013717; f =         -676.9031477
lambda = 0.00045725; f =         -676.9793483
lambda = 0.00088394; f =         -676.9638713
lambda =  0.0005952; f =         -676.9781870
Norm of dx      20.08
Predicted improvement:        0.168990077
lambda =          1; f =         -677.1614496
Norm of dx  0.0029913
Done for param e_a =   0.0657; f = -677.1614
Predicted improvement:        0.204753290
lambda =          1; f =         -677.3823008
Norm of dx  0.0077228
Done for param e_v =   0.1553; f = -677.3823
Predicted improvement:        0.000062693
lambda =          1; f =         -677.3823635
Norm of dx 3.9803e-05
Done for param e_g =   0.0400; f = -677.3824
Predicted improvement:        0.002732508
lambda =          1; f =         -677.3850800
Norm of dx 0.00022201
Done for param e_rer =   0.0332; f = -677.3851
Predicted improvement:        0.000024770
lambda =          1; f =         -677.3851048
Norm of dx 6.3278e-06
Done for param e_yw =   0.0101; f = -677.3851
Predicted improvement:        0.010548296
lambda =          1; f =         -677.3957180
Norm of dx  0.0010079
Done for param alp =   0.3475; f = -677.3957
Predicted improvement:        0.003702547
lambda =          1; f =         -677.3993259
Norm of dx 0.00037128
Done for param bet =   0.9206; f = -677.3993
Predicted improvement:        0.001420749
lambda =          1; f =         -677.4007466
Norm of dx  5.324e-05
Done for param delt =   0.0998; f = -677.4007
Predicted improvement:        0.038118112
lambda =          1; f =         -677.4389936
Norm of dx   0.017869
Done for param sig =   2.1560; f = -677.4390
Predicted improvement:        0.010616022
lambda =          1; f =         -677.4495739
Norm of dx   0.010387
Done for param phi1 =   1.4110; f = -677.4496
Predicted improvement:        0.258625875
lambda =          1; f =         -677.7098399
Norm of dx    0.21772
Done for param phi2 =   4.2987; f = -677.7098
Predicted improvement:        0.362872855
lambda =          1; f =         -678.0485886
Norm of dx   0.019236
Done for param hf =   0.5292; f = -678.0486
Predicted improvement:        0.000504728
lambda =          1; f =         -678.0490935
Norm of dx  0.0023227
Done for param rhoa =   0.4749; f = -678.0491
Predicted improvement:        0.000115875
lambda =          1; f =         -678.0492095
Norm of dx  0.0012116
Done for param rhov =   0.3887; f = -678.0492
Predicted improvement:        0.004245680
lambda =          1; f =         -678.0534469
Norm of dx   0.007781
Done for param rhog =   0.6023; f = -678.0534
Predicted improvement:        0.028420829
lambda =          1; f =         -678.0818869
Norm of dx   0.021512
Done for param rhorer =   0.6312; f = -678.0819
Sequence of univariate steps!!
Actual dxnorm 0.21862
FVAL          -678.0819
Improvement   2.0083
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.148676e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.24994 s.
 
Iteration 6
Near-singular H problem.
Correct for low angle: 1.71412e-23
Predicted improvement: 4764191854939.828125000
lambda =          1; f = 182389264287303761920.0000000
lambda =    0.33333; f = 20265473808958791680.0000000
lambda =    0.11111; f = 2251719311859322368.0000000
lambda =   0.037037; f = 250191034568632384.0000000
lambda =   0.012346; f = 27799003813490952.0000000
lambda =  0.0041152; f = 3088778192342532.0000000
lambda =  0.0013717; f = 343197573874397.0000000
lambda = 0.00045725; f = 38133062745905.4687500
lambda = 0.00015242; f = 4237006632062.3212891
lambda = 5.0805e-05; f = 470778401039.1309814
lambda = 1.6935e-05; f =  52308672948.9404221
lambda =  5.645e-06; f =   5812061612.5240660
lambda = 1.8817e-06; f =    645779836.0407444
lambda = 6.2723e-07; f =     71751318.2050247
lambda = 2.0908e-07; f =      7971301.9976362
lambda = 6.9692e-08; f =       884943.4590626
lambda = 2.3231e-08; f =        97673.5223120
lambda = 7.7435e-09; f =        10233.4717999
lambda = 2.5812e-09; f =          529.2435314

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =    101065592.8118481
lambda = -2.0908e-07; f =     11228459.4437161
lambda = -6.9692e-08; f =      1246855.1145095
lambda = -2.3231e-08; f =       137887.3297530
lambda = -7.7435e-09; f =        14701.8077895
lambda = -2.5812e-09; f =         1025.5678071
Norm of dx 2.0959e+10
Correct for low angle: 0.00439654
Predicted improvement:       29.670466947
lambda =          1; f =          -58.2575238
lambda =    0.33333; f =         -619.7113454
lambda =    0.11111; f =         -673.6524524
lambda =   0.037037; f =         -677.9688768
lambda =   0.012346; f =         -678.0818869
lambda =  0.0041152; f =         -675.3385740
lambda =  0.0013717; f =         -677.8313021
lambda = 0.00045725; f =         -678.0721287
lambda = 0.00015242; f =         -678.0868308
Norm of dx     26.106
Predicted improvement:        0.296128065
lambda =          1; f =         -678.4101140
Norm of dx  0.0040601
Done for param e_a =   0.0698; f = -678.4101
Predicted improvement:        0.236199795
lambda =          1; f =         -678.6657913
Norm of dx  0.0086746
Done for param e_v =   0.1639; f = -678.6658
Predicted improvement:        0.021987431
lambda =          1; f =         -678.6884288
Norm of dx 0.00072621
Done for param e_g =   0.0407; f = -678.6884
Predicted improvement:        0.326694733
lambda =          1; f =         -679.0462921
Norm of dx  0.0021496
Done for param e_rer =   0.0354; f = -679.0463
Predicted improvement:        0.040975525
lambda =          1; f =         -679.0874834
Norm of dx  0.0020028
Done for param alp =   0.3455; f = -679.0875
Predicted improvement:        0.000767797
lambda =          1; f =         -679.0882474
Norm of dx 0.00017219
Done for param bet =   0.9207; f = -679.0882
Predicted improvement:        0.002383045
lambda =          1; f =         -679.0906304
Norm of dx 6.8952e-05
Done for param delt =   0.0998; f = -679.0906
Predicted improvement:        0.010555086
lambda =          1; f =         -679.1012010
Norm of dx  0.0094172
Done for param sig =   2.1642; f = -679.1012
Predicted improvement:        0.004140323
lambda =          1; f =         -679.1053307
Norm of dx  0.0064741
Done for param phi1 =   1.4009; f = -679.1053
Predicted improvement:        0.215116807
lambda =          1; f =         -679.3216623
Norm of dx    0.20551
Done for param phi2 =   4.5031; f = -679.3217
Predicted improvement:        0.394446689
lambda =          1; f =         -679.6881278
Norm of dx   0.019566
Done for param hf =   0.5488; f = -679.6881
Predicted improvement:        0.000017012
lambda =          1; f =         -679.6881448
Norm of dx 0.00042823
Done for param rhoa =   0.4752; f = -679.6881
Predicted improvement:        0.002169492
lambda =          1; f =         -679.6903112
Norm of dx  0.0055991
Done for param rhog =   0.6079; f = -679.6903
Predicted improvement:        0.022984594
lambda =          1; f =         -679.7133104
Norm of dx   0.020095
Done for param rhorer =   0.6111; f = -679.7133
Predicted improvement:        0.000010107
lambda =          1; f =         -679.7133205
Norm of dx 0.00033403
Done for param rhoyw =   0.5538; f = -679.7133
Sequence of univariate steps!!
Actual dxnorm 0.20708
FVAL          -679.7133
Improvement   1.6314
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.798875e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.29418 s.
 
Iteration 7
Correct for low angle: 9.82739e-13
Predicted improvement: 121170652879.297256470
lambda =          1; f = 224561257448037088.0000000
lambda =    0.33333; f = 24951250800651688.0000000
lambda =    0.11111; f = 2772361191102681.0000000
lambda =   0.037037; f = 308040129354432.2500000
lambda =   0.012346; f = 34226680042210.7695312
lambda =  0.0041152; f = 3802964116343.7353516
lambda =  0.0013717; f = 422551457151.7776489
lambda = 0.00045725; f =  46950124394.8713455
lambda = 0.00015242; f =   5216667583.1143360
lambda = 5.0805e-05; f =    579625027.5913119
lambda = 1.6935e-05; f =     64400810.7160755
lambda =  5.645e-06; f =      7154586.7045365
lambda = 1.8817e-06; f =       794198.8786970
lambda = 6.2723e-07; f =        87590.3639364
lambda = 2.0908e-07; f =         9112.0546295
lambda = 6.9692e-08; f =          403.3871960
lambda = 2.3231e-08; f =         -560.7033020
lambda = 7.7435e-09; f =         -666.9072778
lambda = 2.5812e-09; f =         -678.4171789

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =   7242627798.2293863
lambda = -2.0908e-07; f =    804615503.1220348
lambda = -6.9692e-08; f =     89361019.6610081
lambda = -2.3231e-08; f =      9915037.9245416
lambda = -7.7435e-09; f =      1096619.3665468
lambda = -2.5812e-09; f =       119765.9803930
Norm of dx 1.3569e+11
Predicted improvement:       20.825536607
lambda =          1; f =         -461.0269426
lambda =    0.33333; f =         -659.5561276
lambda =    0.11111; f =         -678.4382396
lambda =   0.037037; f =         -679.7129862
lambda =   0.012346; f =         -664.8738457
lambda =  0.0041152; f =         -678.1797133
lambda =  0.0013717; f =         -679.5810126
lambda = 0.00045725; f =         -679.7113159
lambda = 0.00015242; f =         -679.7173299
Norm of dx     15.533
Predicted improvement:        0.294055123
lambda =          1; f =         -680.0379959
Norm of dx  0.0043016
Done for param e_a =   0.0742; f = -680.0380
Predicted improvement:        0.127558320
lambda =          1; f =         -680.1736950
Norm of dx  0.0068934
Done for param e_v =   0.1708; f = -680.1737
Predicted improvement:        0.003872854
lambda =          1; f =         -680.1776172
Norm of dx 0.00031542
Done for param e_g =   0.0410; f = -680.1776
Predicted improvement:        0.187883494
lambda =          1; f =         -680.3797090
Norm of dx  0.0017822
Done for param e_rer =   0.0372; f = -680.3797
Predicted improvement:        0.047201390
lambda =          1; f =         -680.4276932
Norm of dx  0.0021768
Done for param alp =   0.3433; f = -680.4277
Predicted improvement:        0.000016778
lambda =          1; f =         -680.4277100
Norm of dx 2.6083e-05
Done for param bet =   0.9206; f = -680.4277
Predicted improvement:        0.001453810
lambda =          1; f =         -680.4291638
Norm of dx 5.3855e-05
Done for param delt =   0.0998; f = -680.4292
Predicted improvement:        0.001605596
lambda =          1; f =         -680.4307707
Norm of dx  0.0036552
Done for param sig =   2.1673; f = -680.4308
Predicted improvement:        0.001939842
lambda =          1; f =         -680.4327072
Norm of dx  0.0044132
Done for param phi1 =   1.3942; f = -680.4327
Predicted improvement:        0.162915125
lambda =          1; f =         -680.5964053
Norm of dx    0.18412
Done for param phi2 =   4.6873; f = -680.5964
Predicted improvement:        0.371624369
lambda =          1; f =         -680.9421566
Norm of dx   0.018364
Done for param hf =   0.5672; f = -680.9422
Predicted improvement:        0.000132535
lambda =          1; f =         -680.9422891
Norm of dx  0.0012022
Done for param rhoa =   0.4763; f = -680.9423
Predicted improvement:        0.001541442
lambda =          1; f =         -680.9438404
Norm of dx  0.0045392
Done for param rhov =   0.3842; f = -680.9438
Predicted improvement:        0.002818843
lambda =          1; f =         -680.9466546
Norm of dx  0.0063872
Done for param rhog =   0.6144; f = -680.9467
Predicted improvement:        0.013165759
lambda =          1; f =         -680.9598266
Norm of dx   0.015659
Done for param rhorer =   0.5954; f = -680.9598
Sequence of univariate steps!!
Actual dxnorm 0.1863
FVAL          -680.9598
Improvement   1.2465
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  5.882966e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.26009 s.
 
Iteration 8
Near-singular H problem.
Correct for low angle: 8.63777e-23
Predicted improvement: 1158579097189.054931641
lambda =          1; f = 36578509874046693376.0000000
lambda =    0.33333; f = 4064278874548765184.0000000
lambda =    0.11111; f = 451586541501424832.0000000
lambda =   0.037037; f = 50176282350678616.0000000
lambda =   0.012346; f = 5575142470618807.0000000
lambda =  0.0041152; f = 619460270249496.6250000
lambda =  0.0013717; f = 68828917494977.5937500
lambda = 0.00045725; f = 7647657025163.0498047
lambda = 0.00015242; f = 849739510968.3765869
lambda = 5.0805e-05; f =  94415447986.0969391
lambda = 1.6935e-05; f =  10490587185.3204918
lambda =  5.645e-06; f =   1165614346.8217516
lambda = 1.8817e-06; f =    129510151.9616411
lambda = 6.2723e-07; f =     14388763.0793230
lambda = 2.0908e-07; f =      1597930.7918427
lambda = 6.9692e-08; f =       176871.5095426
lambda = 2.3231e-08; f =        19024.0102077
lambda = 7.7435e-09; f =         1501.2681357
lambda = 2.5812e-09; f =         -440.5004429

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     11785012.4444272
lambda = -2.0908e-07; f =      1308654.7664670
lambda = -6.9692e-08; f =       144739.0551483
lambda = -2.3231e-08; f =        15456.4307830
lambda = -7.7435e-09; f =         1105.4759288
lambda = -2.5812e-09; f =         -484.4808818
Norm of dx 8.1571e+09
Predicted improvement:       17.960371248
lambda =          1; f =         -582.1528346
lambda =    0.33333; f =         -672.3737615
lambda =    0.11111; f =         -680.5718044
lambda =   0.037037; f =         -680.9597831
lambda =   0.012346; f =         -670.9221688
lambda =  0.0041152; f =         -679.9434255
lambda =  0.0013717; f =         -680.8797444
lambda = 0.00045725; f =         -680.9618783
lambda = 0.00015242; f =         -680.9637045
lambda = 0.00029465; f =         -680.9644423
Norm of dx     11.908
Predicted improvement:        0.247691423
lambda =          1; f =         -681.2331989
Norm of dx  0.0042281
Done for param e_a =   0.0785; f = -681.2332
Predicted improvement:        0.063531287
lambda =          1; f =         -681.2997641
Norm of dx  0.0051682
Done for param e_v =   0.1760; f = -681.2998
Predicted improvement:        0.001083790
lambda =          1; f =         -681.3008553
Norm of dx 0.00016905
Done for param e_g =   0.0412; f = -681.3009
Predicted improvement:        0.104793042
lambda =          1; f =         -681.4119933
Norm of dx  0.0014262
Done for param e_rer =   0.0386; f = -681.4120
Predicted improvement:        0.045044552
lambda =          1; f =         -681.4576709
Norm of dx   0.002164
Done for param alp =   0.3411; f = -681.4577
Predicted improvement:        0.000879331
lambda =          1; f =         -681.4585581
Norm of dx 0.00019229
Done for param bet =   0.9203; f = -681.4586
Predicted improvement:        0.004540971
lambda =          1; f =         -681.4630991
Norm of dx 9.5177e-05
Done for param delt =   0.0998; f = -681.4631
Predicted improvement:        0.000014754
lambda =          1; f =         -681.4631138
Norm of dx  0.0003475
Done for param sig =   2.1670; f = -681.4631
Predicted improvement:        0.000414321
lambda =          1; f =         -681.4635277
Norm of dx  0.0020275
Done for param phi1 =   1.3891; f = -681.4635
Predicted improvement:        0.117319017
lambda =          1; f =         -681.5813138
Norm of dx    0.16008
Done for param phi2 =   4.8490; f = -681.5813
Predicted improvement:        0.332146746
lambda =          1; f =         -681.8914865
Norm of dx   0.016738
Done for param hf =   0.5840; f = -681.8915
Predicted improvement:        0.000150718
lambda =          1; f =         -681.8916371
Norm of dx  0.0012893
Done for param rhoa =   0.4774; f = -681.8916
Predicted improvement:        0.006561064
lambda =          1; f =         -681.8982839
Norm of dx  0.0094407
Done for param rhov =   0.3747; f = -681.8983
Predicted improvement:        0.003000919
lambda =          1; f =         -681.9012797
Norm of dx  0.0065818
Done for param rhog =   0.6210; f = -681.9013
Predicted improvement:        0.007481754
lambda =          1; f =         -681.9087641
Norm of dx   0.012066
Done for param rhorer =   0.5833; f = -681.9088
Sequence of univariate steps!!
Actual dxnorm 0.16364
FVAL          -681.9088
Improvement   0.94894
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.601576e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.27227 s.
 
Iteration 9
Correct for low angle: 3.72756e-13
Predicted improvement: 239128654696.816802979
lambda =          1; f = 179023297499301320589312.0000000
lambda =    0.33333; f = 19891477499324156346368.0000000
lambda =    0.11111; f = 2210164166392169889792.0000000
lambda =   0.037037; f = 245573796199328808960.0000000
lambda =   0.012346; f = 27285977333325012992.0000000
lambda =  0.0041152; f = 3031775251873012224.0000000
lambda =  0.0013717; f = 336863914413005056.0000000
lambda = 0.00045725; f = 37429323003075408.0000000
lambda = 0.00015242; f = 4158813393477383.0000000
lambda = 5.0805e-05; f = 462090285875646.1250000
lambda = 1.6935e-05; f = 51343334704431.2343750
lambda =  5.645e-06; f = 5704804835807.4833984
lambda = 1.8817e-06; f = 633863826464.0906982
lambda = 6.2723e-07; f =  70428187815.9144440
lambda = 2.0908e-07; f =   7824978392.3498840
lambda = 6.9692e-08; f =    869316376.1837937
lambda = 2.3231e-08; f =     96548421.6286601
lambda = 7.7435e-09; f =     10713109.0717955
lambda = 2.5812e-09; f =      1185116.3123417

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =       708152.9122944
lambda = -2.0908e-07; f =        78029.1661143
lambda = -6.9692e-08; f =         8047.8366212
lambda = -2.3231e-08; f =          282.9400383
lambda = -7.7435e-09; f =         -576.2240173
lambda = -2.5812e-09; f =         -670.5903302
Norm of dx 4.2311e+11
Predicted improvement:       15.543475760
lambda =          1; f =         -674.7269144
lambda =    0.33333; f =         -681.6132172
lambda =    0.11111; f =         -681.9083118
lambda =   0.037037; f =         -681.9087633
lambda =   0.012346; f =         -679.0973491
lambda =  0.0041152; f =         -681.6817038
lambda =  0.0013717; f =         -681.9119643
lambda = 0.00045725; f =         -681.9185959
Norm of dx     12.296
Predicted improvement:        0.191116110
lambda =          1; f =         -682.1242895
Norm of dx  0.0039743
Done for param e_a =   0.0825; f = -682.1243
Predicted improvement:        0.027510808
lambda =          1; f =         -682.1526808
Norm of dx  0.0035655
Done for param e_v =   0.1797; f = -682.1527
Predicted improvement:        0.000194840
lambda =          1; f =         -682.1528762
Norm of dx 7.2214e-05
Done for param e_g =   0.0412; f = -682.1529
Predicted improvement:        0.058732878
lambda =          1; f =         -682.2143244
Norm of dx  0.0011271
Done for param e_rer =   0.0398; f = -682.2143
Predicted improvement:        0.037344698
lambda =          1; f =         -682.2521712
Norm of dx  0.0019996
Done for param alp =   0.3392; f = -682.2522
Predicted improvement:        0.002548204
lambda =          1; f =         -682.2547565
Norm of dx 0.00033358
Done for param bet =   0.9198; f = -682.2548
Predicted improvement:        0.003453030
lambda =          1; f =         -682.2582096
Norm of dx 8.2993e-05
Done for param delt =   0.0998; f = -682.2582
Predicted improvement:        0.000551235
lambda =          1; f =         -682.2587603
Norm of dx  0.0021038
Done for param sig =   2.1653; f = -682.2588
Predicted improvement:        0.000130339
lambda =          1; f =         -682.2588905
Norm of dx  0.0011305
Done for param phi1 =   1.3865; f = -682.2589
Predicted improvement:        0.077294903
lambda =          1; f =         -682.3364294
Norm of dx    0.13255
Done for param phi2 =   4.9869; f = -682.3364
Predicted improvement:        0.280690892
lambda =          1; f =         -682.6000434
Norm of dx   0.014819
Done for param hf =   0.5990; f = -682.6000
Predicted improvement:        0.000095018
lambda =          1; f =         -682.6001384
Norm of dx  0.0010287
Done for param rhoa =   0.4781; f = -682.6001
Predicted improvement:        0.012422060
lambda =          1; f =         -682.6127767
Norm of dx   0.013128
Done for param rhov =   0.3615; f = -682.6128
Predicted improvement:        0.002807474
lambda =          1; f =         -682.6155795
Norm of dx  0.0063498
Done for param rhog =   0.6275; f = -682.6156
Predicted improvement:        0.004299548
lambda =          1; f =         -682.6198801
Norm of dx  0.0092997
Done for param rhorer =   0.5740; f = -682.6199
Sequence of univariate steps!!
Actual dxnorm 0.14002
FVAL          -682.6199
Improvement   0.71112
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.008234e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.33289 s.
 
Iteration 10
Near-singular H problem.
Correct for low angle: 2.11573e-22
Predicted improvement: 553377691997.806884766
lambda =          1; f = 24146692064099831808.0000000
lambda =    0.33333; f = 2682965784622068224.0000000
lambda =    0.11111; f = 298107309309813440.0000000
lambda =   0.037037; f = 33123034336877184.0000000
lambda =   0.012346; f = 3680337138248221.5000000
lambda =  0.0041152; f = 408926345262621.0000000
lambda =  0.0013717; f = 45436259440460.7578125
lambda = 0.00045725; f = 5048472889334.9140625
lambda = 0.00015242; f = 560941304470.0841064
lambda = 5.0805e-05; f =  62326768644.9705048
lambda = 1.6935e-05; f =   6925181791.2595825
lambda =  5.645e-06; f =    769459331.2795622
lambda = 1.8817e-06; f =     85493306.6110689
lambda = 6.2723e-07; f =      9498127.4984059
lambda = 2.0908e-07; f =      1054567.3249444
lambda = 6.9692e-08; f =       116510.1622204
lambda = 2.3231e-08; f =        12320.2613216
lambda = 7.7435e-09; f =          756.4010142
lambda = 2.5812e-09; f =         -524.2535074

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      5435536.9563508
lambda = -2.0908e-07; f =       603194.9135671
lambda = -6.9692e-08; f =        66366.3283425
lambda = -2.3231e-08; f =         6751.4772347
lambda = -7.7435e-09; f =          138.4414030
lambda = -2.5812e-09; f =         -592.8507025
Norm of dx 6.1617e+09
Predicted improvement:       14.053296405
lambda =          1; f =         -682.4775915
lambda =    0.33333; f =         -682.6076402
lambda =    0.11111; f =         -682.6193202
lambda =   0.037037; f =         -677.1757793
lambda =   0.012346; f =         -682.2468184
lambda =  0.0041152; f =         -682.6555503
Norm of dx     15.872
Predicted improvement:        0.136118276
lambda =          1; f =         -682.8005440
Norm of dx   0.003591
Done for param e_a =   0.0866; f = -682.8005
Predicted improvement:        0.009705680
lambda =          1; f =         -682.8104426
Norm of dx  0.0022125
Done for param e_v =   0.1839; f = -682.8104
Predicted improvement:        0.000124123
lambda =          1; f =         -682.8105670
Norm of dx 5.7694e-05
Done for param e_g =   0.0413; f = -682.8106
Predicted improvement:        0.031412390
lambda =          1; f =         -682.8430705
Norm of dx 0.00086407
Done for param e_rer =   0.0409; f = -682.8431
Predicted improvement:        0.040148066
lambda =          1; f =         -682.8836269
Norm of dx  0.0021148
Done for param alp =   0.3392; f = -682.8836
Predicted improvement:        0.001844597
lambda =          1; f =         -682.8854796
Norm of dx 0.00029382
Done for param bet =   0.9179; f = -682.8855
Predicted improvement:        0.054622362
lambda =          1; f =         -682.9401010
Norm of dx 0.00033006
Done for param delt =   0.0998; f = -682.9401
Predicted improvement:        0.008031738
lambda =          1; f =         -682.9481162
Norm of dx  0.0079724
Done for param sig =   2.1674; f = -682.9481
Predicted improvement:        0.004209387
lambda =          1; f =         -682.9523073
Norm of dx  0.0064147
Done for param phi1 =   1.3871; f = -682.9523
Predicted improvement:        0.029998717
lambda =          1; f =         -682.9823633
Norm of dx   0.084397
Done for param phi2 =   5.1353; f = -682.9824
Predicted improvement:        0.222027494
lambda =          1; f =         -683.1924150
Norm of dx   0.012645
Done for param hf =   0.6136; f = -683.1924
Predicted improvement:        0.000646979
lambda =          1; f =         -683.1930616
Norm of dx  0.0027018
Done for param rhoa =   0.4786; f = -683.1931
Predicted improvement:        0.014035234
lambda =          1; f =         -683.2073463
Norm of dx   0.014185
Done for param rhov =   0.3470; f = -683.2073
Predicted improvement:        0.003217957
lambda =          1; f =         -683.2105585
Norm of dx  0.0067715
Done for param rhog =   0.6352; f = -683.2106
Predicted improvement:        0.003361111
lambda =          1; f =         -683.2139203
Norm of dx  0.0083431
Done for param rhorer =   0.5649; f = -683.2139
Sequence of univariate steps!!
Actual dxnorm 0.15041
FVAL          -683.2139
Improvement   0.59404
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.111770e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31281 s.
 
Iteration 11
Correct for low angle: 4.5061e-13
Predicted improvement: 191633680376.681884766
lambda =          1; f = 5309577282715753472.0000000
lambda =    0.33333; f = 589953031270465664.0000000
lambda =    0.11111; f = 65550336760363768.0000000
lambda =   0.037037; f = 7283370735329219.0000000
lambda =   0.012346; f = 809263409762077.1250000
lambda =  0.0041152; f = 89918154881664.7968750
lambda =  0.0013717; f = 9990905511375.6601562
lambda = 0.00045725; f = 1110100416447.5979004
lambda = 0.00015242; f = 123344425008.2089996
lambda = 5.0805e-05; f =  13704913809.4237061
lambda = 1.6935e-05; f =   1522760366.9525912
lambda =  5.645e-06; f =    169192585.0685876
lambda = 1.8817e-06; f =     18797769.8559726
lambda = 6.2723e-07; f =      2087768.0874739
lambda = 2.0908e-07; f =       231278.9635275
lambda = 6.9692e-08; f =        25061.6018773
lambda = 2.3231e-08; f =         2168.2523383
lambda = 7.7435e-09; f =         -368.9985290
lambda = 2.5812e-09; f =         -648.9179216

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f = 125417996990.3828430
lambda = -2.0908e-07; f =  13934831698.4803219
lambda = -6.9692e-08; f =   1548147134.5520320
lambda = -2.3231e-08; f =    171960116.9506629
lambda = -7.7435e-09; f =     19087537.3762440
lambda = -2.5812e-09; f =      2114058.0161456
Norm of dx 5.6463e+11
Predicted improvement:       12.402231841
lambda =          1; f =         -467.6636145
lambda =    0.33333; f =         -664.3292548
lambda =    0.11111; f =         -682.2183755
lambda =   0.037037; f =         -683.2138834
lambda =   0.012346; f =         -672.8626765
lambda =  0.0041152; f =         -682.1320992
lambda =  0.0013717; f =         -683.1164008
lambda = 0.00045725; f =         -683.2106459
lambda = 0.00015242; f =         -683.2160769
Norm of dx     15.948
Predicted improvement:        0.086774796
lambda =          1; f =         -683.3075459
Norm of dx  0.0030331
Done for param e_a =   0.0897; f = -683.3075
Predicted improvement:        0.000617039
lambda =          1; f =         -683.3081661
Norm of dx 0.00057249
Done for param e_v =   0.1844; f = -683.3082
Predicted improvement:        0.000164259
lambda =          1; f =         -683.3083299
Norm of dx 6.6759e-05
Done for param e_g =   0.0412; f = -683.3083
Predicted improvement:        0.017678436
lambda =          1; f =         -683.3264759
Norm of dx 0.00066796
Done for param e_rer =   0.0416; f = -683.3265
Predicted improvement:        0.023251274
lambda =          1; f =         -683.3499153
Norm of dx  0.0016285
Done for param alp =   0.3376; f = -683.3499
Predicted improvement:        0.003499203
lambda =          1; f =         -683.3534323
Norm of dx 0.00041074
Done for param bet =   0.9174; f = -683.3534
Predicted improvement:        0.001043888
lambda =          1; f =         -683.3544761
Norm of dx 4.5626e-05
Done for param delt =   0.0998; f = -683.3545
Predicted improvement:        0.006049631
lambda =          1; f =         -683.3605189
Norm of dx  0.0068294
Done for param sig =   2.1595; f = -683.3605
Predicted improvement:        0.000075009
lambda =          1; f =         -683.3605939
Norm of dx 0.00084801
Done for param phi1 =   1.3842; f = -683.3606
Predicted improvement:        0.025253213
lambda =          1; f =         -683.3858909
Norm of dx   0.078177
Done for param phi2 =   5.2129; f = -683.3859
Predicted improvement:        0.179797376
lambda =          1; f =         -683.5569873
Norm of dx   0.011012
Done for param hf =   0.6247; f = -683.5570
Predicted improvement:        0.000063375
lambda =          1; f =         -683.5570506
Norm of dx 0.00084647
Done for param rhoa =   0.4793; f = -683.5571
Predicted improvement:        0.022135615
lambda =          1; f =         -683.5796475
Norm of dx   0.017918
Done for param rhov =   0.3291; f = -683.5796
Predicted improvement:        0.001947176
lambda =          1; f =         -683.5815919
Norm of dx  0.0052454
Done for param rhog =   0.6405; f = -683.5816
Predicted improvement:        0.001037438
lambda =          1; f =         -683.5826295
Norm of dx  0.0046803
Done for param rhorer =   0.5602; f = -683.5826
Sequence of univariate steps!!
Actual dxnorm 0.081268
FVAL          -683.5826
Improvement   0.36871
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.244644e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31124 s.
 
Iteration 12
Correct for low angle: 4.03037e-13
Predicted improvement: 237376198670.547729492
lambda =          1; f = 790688140630782870814720.0000000
lambda =    0.33333; f = 87854237846607516139520.0000000
lambda =    0.11111; f = 9761581982537318662144.0000000
lambda =   0.037037; f = 1084620220142232666112.0000000
lambda =   0.012346; f = 120513357747017498624.0000000
lambda =  0.0041152; f = 13390373067480625152.0000000
lambda =  0.0013717; f = 1487819224546299648.0000000
lambda = 0.00045725; f = 165313245447220512.0000000
lambda = 0.00015242; f = 18368137808160568.0000000
lambda = 5.0805e-05; f = 2040904009285030.5000000
lambda = 1.6935e-05; f = 226767048268486.9062500
lambda =  5.645e-06; f = 25196317404673.2539062
lambda = 1.8817e-06; f = 2799583725072.4697266
lambda = 6.2723e-07; f = 311062492054.1718140
lambda = 2.0908e-07; f =  34561709956.2218094
lambda = 6.9692e-08; f =   3839926542.9957500
lambda = 2.3231e-08; f =    426570288.8458869
lambda = 7.7435e-09; f =     47366894.8585567
lambda = 2.5812e-09; f =      5252654.9823106

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2323534.9878013
lambda = -2.0908e-07; f =       257439.0248630
lambda = -6.9692e-08; f =        27955.8241379
lambda = -2.3231e-08; f =         2485.3631837
lambda = -7.7435e-09; f =         -335.4638802
lambda = -2.5812e-09; f =         -645.8998498
Norm of dx 8.8921e+11
Predicted improvement:       11.396499895
lambda =          1; f =         -683.4456742
lambda =    0.33333; f =         -683.5702935
lambda =    0.11111; f =         -683.5820163
lambda =   0.037037; f =         -669.4289604
lambda =   0.012346; f =         -682.2028567
lambda =  0.0041152; f =         -683.4920168
lambda =  0.0013717; f =         -683.5934108
Norm of dx     21.849
Predicted improvement:        0.057603425
lambda =          1; f =         -683.6536117
Norm of dx  0.0025832
Done for param e_a =   0.0923; f = -683.6536
Predicted improvement:        0.000057345
lambda =          1; f =         -683.6536691
Norm of dx 0.00017659
Done for param e_v =   0.1856; f = -683.6537
Predicted improvement:        0.000081111
lambda =          1; f =         -683.6537501
Norm of dx 4.6799e-05
Done for param e_g =   0.0411; f = -683.6538
Predicted improvement:        0.008875987
lambda =          1; f =         -683.6627944
Norm of dx 0.00048565
Done for param e_rer =   0.0421; f = -683.6628
Predicted improvement:        0.018117780
lambda =          1; f =         -683.6810362
Norm of dx  0.0014518
Done for param alp =   0.3373; f = -683.6810
Predicted improvement:        0.003473959
lambda =          1; f =         -683.6845279
Norm of dx 0.00041556
Done for param bet =   0.9165; f = -683.6845
Predicted improvement:        0.010310199
lambda =          1; f =         -683.6948382
Norm of dx 0.00014338
Done for param delt =   0.0998; f = -683.6948
Predicted improvement:        0.009808718
lambda =          1; f =         -683.7046342
Norm of dx   0.008621
Done for param sig =   2.1570; f = -683.7046
Predicted improvement:        0.003274738
lambda =          1; f =         -683.7078982
Norm of dx  0.0055931
Done for param phi1 =   1.3896; f = -683.7079
Predicted improvement:        0.008534797
lambda =          1; f =         -683.7164414
Norm of dx   0.045913
Done for param phi2 =   5.2859; f = -683.7164
Predicted improvement:        0.125699943
lambda =          1; f =         -683.8370984
Norm of dx  0.0089053
Done for param hf =   0.6342; f = -683.8371
Predicted improvement:        0.018054451
lambda =          1; f =         -683.8554655
Norm of dx   0.016403
Done for param rhov =   0.3127; f = -683.8555
Predicted improvement:        0.001322026
lambda =          1; f =         -683.8567860
Norm of dx  0.0043064
Done for param rhog =   0.6450; f = -683.8568
Predicted improvement:        0.000822834
lambda =          1; f =         -683.8576089
Norm of dx  0.0041979
Done for param rhorer =   0.5557; f = -683.8576
Sequence of univariate steps!!
Actual dxnorm 0.076013
FVAL          -683.8576
Improvement   0.27498
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  8.017925e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.30611 s.
 
Iteration 13
Correct for low angle: 1.22886e-12
Predicted improvement: 50338173184.664527893
lambda =          1; f = 55520935341693027221504.0000000
lambda =    0.33333; f = 6168992815410515542016.0000000
lambda =    0.11111; f = 685443646045672308736.0000000
lambda =   0.037037; f = 76160405079168679936.0000000
lambda =   0.012346; f = 8462267218679685120.0000000
lambda =  0.0041152; f = 940251909073613056.0000000
lambda =  0.0013717; f = 104472432970505984.0000000
lambda = 0.00045725; f = 11608047650831406.0000000
lambda = 0.00015242; f = 1289782919980010.0000000
lambda = 5.0805e-05; f = 143309162552521.3750000
lambda = 1.6935e-05; f = 15923223357022.7636719
lambda =  5.645e-06; f = 1769241397078.4748535
lambda = 1.8817e-06; f = 196580496191.9533386
lambda = 6.2723e-07; f =  21841649868.9357758
lambda = 2.0908e-07; f =   2426640424.8694482
lambda = 6.9692e-08; f =    269556461.6455280
lambda = 2.3231e-08; f =     29926901.8123386
lambda = 7.7435e-09; f =      3316873.7340213
lambda = 2.5812e-09; f =       365363.1431886

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =       148412.2048876
lambda = -2.0908e-07; f =        15848.3197436
lambda = -6.9692e-08; f =         1142.1084096
lambda = -2.3231e-08; f =         -484.2119928
lambda = -7.7435e-09; f =         -662.4146888
lambda = -2.5812e-09; f =         -681.6695980
Norm of dx 2.3563e+11
Predicted improvement:        6.882694112
lambda =          1; f =         -683.7353793
lambda =    0.33333; f =         -683.8466241
lambda =    0.11111; f =         -683.8570695
lambda =   0.037037; f =         -665.1814048
lambda =   0.012346; f =         -681.8994302
lambda =  0.0041152; f =         -683.6779042
lambda =  0.0013717; f =         -683.8502351
lambda = 0.00045725; f =         -683.8609873
Norm of dx     11.615
Predicted improvement:        0.037164874
lambda =          1; f =         -683.8995369
Norm of dx   0.002152
Done for param e_a =   0.0944; f = -683.8995
Predicted improvement:        0.000241539
lambda =          1; f =         -683.8997776
Norm of dx 0.00036477
Done for param e_v =   0.1854; f = -683.8998
Predicted improvement:        0.000085522
lambda =          1; f =         -683.8998630
Norm of dx 4.8001e-05
Done for param e_g =   0.0411; f = -683.8999
Predicted improvement:        0.005223354
lambda =          1; f =         -683.9051632
Norm of dx 0.00037864
Done for param e_rer =   0.0425; f = -683.9052
Predicted improvement:        0.010963938
lambda =          1; f =         -683.9161922
Norm of dx  0.0011385
Done for param alp =   0.3366; f = -683.9162
Predicted improvement:        0.004195265
lambda =          1; f =         -683.9204112
Norm of dx 0.00046207
Done for param bet =   0.9159; f = -683.9204
Predicted improvement:        0.002735769
lambda =          1; f =         -683.9231470
Norm of dx 7.3857e-05
Done for param delt =   0.0998; f = -683.9231
Predicted improvement:        0.007240901
lambda =          1; f =         -683.9303794
Norm of dx   0.007332
Done for param sig =   2.1505; f = -683.9304
Predicted improvement:        0.000843197
lambda =          1; f =         -683.9312224
Norm of dx  0.0028179
Done for param phi1 =   1.3894; f = -683.9312
Predicted improvement:        0.007989637
lambda =          1; f =         -683.9392213
Norm of dx   0.044672
Done for param phi2 =   5.3351; f = -683.9392
Predicted improvement:        0.095978410
lambda =          1; f =         -684.0318514
Norm of dx  0.0075793
Done for param hf =   0.6419; f = -684.0319
Predicted improvement:        0.000067062
lambda =          1; f =         -684.0319185
Norm of dx 0.00087167
Done for param rhoa =   0.4779; f = -684.0319
Predicted improvement:        0.017710256
lambda =          1; f =         -684.0499034
Norm of dx   0.016346
Done for param rhov =   0.2965; f = -684.0499
Predicted improvement:        0.001077460
lambda =          1; f =         -684.0509797
Norm of dx  0.0038777
Done for param rhog =   0.6489; f = -684.0510
Predicted improvement:        0.000321480
lambda =          1; f =         -684.0513012
Norm of dx  0.0026384
Done for param rhorer =   0.5530; f = -684.0513
Sequence of univariate steps!!
Actual dxnorm 0.053046
FVAL          -684.0513
Improvement   0.19369
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.380974e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.30793 s.
 
Iteration 14
Correct for low angle: 7.7465e-13
Predicted improvement: 76289284628.828582764
lambda =          1; f = 201197692180061434675200.0000000
lambda =    0.33333; f = 22355299130483740246016.0000000
lambda =    0.11111; f = 2483922125397901705216.0000000
lambda =   0.037037; f = 275991347195966259200.0000000
lambda =   0.012346; f = 30665705220507160576.0000000
lambda =  0.0041152; f = 3407300572226650112.0000000
lambda =  0.0013717; f = 378588949859727488.0000000
lambda = 0.00045725; f = 42065438003335864.0000000
lambda = 0.00015242; f = 4673937265936753.0000000
lambda = 5.0805e-05; f = 519326266218316.4375000
lambda = 1.6935e-05; f = 57702886247126.3046875
lambda =  5.645e-06; f = 6411421064317.3476562
lambda = 1.8817e-06; f = 712376537556.8519287
lambda = 6.2723e-07; f =  79151754652.2330322
lambda = 2.0908e-07; f =   8794241018.6224327
lambda = 6.9692e-08; f =    977004696.4336251
lambda = 2.3231e-08; f =    108511280.3737270
lambda = 7.7435e-09; f =     12041477.7085985
lambda = 2.5812e-09; f =      1332432.4665619

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =       493910.6103001
lambda = -2.0908e-07; f =        54198.8769952
lambda = -6.9692e-08; f =         5390.4544577
lambda = -2.3231e-08; f =          -16.5580291
lambda = -7.7435e-09; f =         -611.9553367
lambda = -2.5812e-09; f =         -676.4559680
Norm of dx 4.4855e+11
Predicted improvement:        9.350983167
lambda =          1; f =         -683.8290349
lambda =    0.33333; f =         -684.0302014
lambda =    0.11111; f =         -684.0498705
lambda =   0.037037; f =         -684.0512972
lambda =   0.012346; f =         -684.0058162
lambda =  0.0041152; f =         -684.0975846
Norm of dx     12.215
Predicted improvement:        0.023833282
lambda =          1; f =         -684.1221379
Norm of dx  0.0017788
Done for param e_a =   0.0963; f = -684.1221
Predicted improvement:        0.000279747
lambda =          1; f =         -684.1224167
Norm of dx 0.00039563
Done for param e_v =   0.1868; f = -684.1224
Predicted improvement:        0.000025071
lambda =          1; f =         -684.1224417
Norm of dx 2.5929e-05
Done for param e_g =   0.0410; f = -684.1224
Predicted improvement:        0.002479259
lambda =          1; f =         -684.1249463
Norm of dx 0.00026592
Done for param e_rer =   0.0431; f = -684.1249
Predicted improvement:        0.016225343
lambda =          1; f =         -684.1412909
Norm of dx  0.0013998
Done for param alp =   0.3387; f = -684.1413
Predicted improvement:        0.000874480
lambda =          1; f =         -684.1421662
Norm of dx 0.00021554
Done for param bet =   0.9137; f = -684.1422
Predicted improvement:        0.004652885
lambda =          1; f =         -684.1468208
Norm of dx 9.6312e-05
Done for param delt =   0.0999; f = -684.1468
Predicted improvement:        0.007868738
lambda =          1; f =         -684.1546795
Norm of dx  0.0075834
Done for param sig =   2.1462; f = -684.1547
Predicted improvement:        0.002608124
lambda =          1; f =         -684.1572799
Norm of dx  0.0049501
Done for param phi1 =   1.3939; f = -684.1573
Predicted improvement:        0.001004804
lambda =          1; f =         -684.1582850
Norm of dx   0.015986
Done for param phi2 =   5.4001; f = -684.1583
Predicted improvement:        0.063182183
lambda =          1; f =         -684.2196908
Norm of dx   0.005971
Done for param hf =   0.6499; f = -684.2197
Predicted improvement:        0.000101724
lambda =          1; f =         -684.2197925
Norm of dx  0.0010762
Done for param rhoa =   0.4768; f = -684.2198
Predicted improvement:        0.011809863
lambda =          1; f =         -684.2317362
Norm of dx   0.013463
Done for param rhov =   0.2831; f = -684.2317
Predicted improvement:        0.001098758
lambda =          1; f =         -684.2328338
Norm of dx   0.003903
Done for param rhog =   0.6533; f = -684.2328
Predicted improvement:        0.000459483
lambda =          1; f =         -684.2332933
Norm of dx  0.0031733
Done for param rhorer =   0.5490; f = -684.2333
Sequence of univariate steps!!
Actual dxnorm 0.067475
FVAL          -684.2333
Improvement   0.18199
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  4.635475e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.3038 s.
 
Iteration 15
Near-singular H problem.
Correct for low angle: 1.86608e-22
Predicted improvement: 346003101519.363586426
lambda =          1; f = 145788659891717079040.0000000
lambda =    0.33333; f = 16198739987038238720.0000000
lambda =    0.11111; f = 1799859998249692672.0000000
lambda =   0.037037; f = 199984444146595136.0000000
lambda =   0.012346; f = 22220493759608816.0000000
lambda =  0.0041152; f = 2468943739581477.0000000
lambda =  0.0013717; f = 274327078346598.5312500
lambda = 0.00045725; f = 30480785206183.4726562
lambda = 0.00015242; f = 3386753485809.1201172
lambda = 5.0805e-05; f = 376305800471.8190308
lambda = 1.6935e-05; f =  41811707743.0635147
lambda =  5.645e-06; f =   4645728950.1833210
lambda = 1.8817e-06; f =    516186254.4127048
lambda = 6.2723e-07; f =     57351678.2509560
lambda = 2.0908e-07; f =      6371225.6654344
lambda = 6.9692e-08; f =       707115.7354141
lambda = 2.3231e-08; f =        77897.4447274
lambda = 7.7435e-09; f =         8026.6928330
lambda = 2.5812e-09; f =          277.3866892

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     15705634.5307790
lambda = -2.0908e-07; f =      1743970.9026977
lambda = -6.9692e-08; f =       193002.9663931
lambda = -2.3231e-08; f =        20782.5328176
lambda = -7.7435e-09; f =         1683.3747954
lambda = -2.5812e-09; f =         -426.6053043
Norm of dx 1.3628e+10
Predicted improvement:        8.152445070
lambda =          1; f =           91.3655498
lambda =    0.33333; f =         -622.8083732
lambda =    0.11111; f =         -680.7479226
lambda =   0.037037; f =         -684.1771879
lambda =   0.012346; f =         -668.4305534
lambda =  0.0041152; f =         -682.5224686
lambda =  0.0013717; f =         -684.0580985
lambda = 0.00045725; f =         -684.2187953
lambda = 0.00015242; f =         -684.2333393
lambda = 5.0805e-05; f =         -684.2338507
Norm of dx     30.291
Predicted improvement:        0.013549843
lambda =          1; f =         -684.2477143
Norm of dx  0.0013764
Done for param e_a =   0.0977; f = -684.2477
Predicted improvement:        0.001314902
lambda =          1; f =         -684.2490190
Norm of dx 0.00085895
Done for param e_v =   0.1859; f = -684.2490
Predicted improvement:        0.000279842
lambda =          1; f =         -684.2492979
Norm of dx 8.6764e-05
Done for param e_g =   0.0410; f = -684.2493
Predicted improvement:        0.001017424
lambda =          1; f =         -684.2503220
Norm of dx   0.000172
Done for param e_rer =   0.0432; f = -684.2503
Predicted improvement:        0.007365859
lambda =          1; f =         -684.2577244
Norm of dx 0.00094936
Done for param alp =   0.3378; f = -684.2577
Predicted improvement:        0.001533452
lambda =          1; f =         -684.2592644
Norm of dx  0.0002874
Done for param bet =   0.9134; f = -684.2593
Predicted improvement:        0.000127704
lambda =          1; f =         -684.2593921
Norm of dx 1.5955e-05
Done for param delt =   0.0999; f = -684.2594
Predicted improvement:        0.005211439
lambda =          1; f =         -684.2645974
Norm of dx   0.006117
Done for param sig =   2.1394; f = -684.2646
Predicted improvement:        0.000049524
lambda =          1; f =         -684.2646469
Norm of dx 0.00067765
Done for param phi1 =   1.3921; f = -684.2646
Predicted improvement:        0.002767927
lambda =          1; f =         -684.2674164
Norm of dx   0.026589
Done for param phi2 =   5.4257; f = -684.2674
Predicted improvement:        0.049301013
lambda =          1; f =         -684.3154981
Norm of dx  0.0051761
Done for param hf =   0.6551; f = -684.3155
Predicted improvement:        0.000010072
lambda =          1; f =         -684.3155082
Norm of dx 0.00033802
Done for param rhoa =   0.4764; f = -684.3155
Predicted improvement:        0.011703609
lambda =          1; f =         -684.3273277
Norm of dx   0.013401
Done for param rhov =   0.2697; f = -684.3273
Predicted improvement:        0.000603632
lambda =          1; f =         -684.3279308
Norm of dx  0.0028848
Done for param rhog =   0.6562; f = -684.3279
Predicted improvement:        0.000025445
lambda =          1; f =         -684.3279563
Norm of dx 0.00074894
Done for param rhorer =   0.5482; f = -684.3280
Sequence of univariate steps!!
Actual dxnorm 0.03044
FVAL          -684.328
Improvement   0.094663
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.070594e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31117 s.
 
Iteration 16
Correct for low angle: 7.17311e-13
Predicted improvement: 80079039396.279434204
lambda =          1; f = 643502678829026538160128.0000000
lambda =    0.33333; f = 71500297646535386071040.0000000
lambda =    0.11111; f = 7944477515903626379264.0000000
lambda =   0.037037; f = 882719723863264067584.0000000
lambda =   0.012346; f = 98079969276131295232.0000000
lambda =  0.0041152; f = 10897774350011527168.0000000
lambda =  0.0013717; f = 1210863812000260608.0000000
lambda = 0.00045725; f = 134540421999688640.0000000
lambda = 0.00015242; f = 14948935259110810.0000000
lambda = 5.0805e-05; f = 1660992633690017.5000000
lambda = 1.6935e-05; f = 184554679450324.7187500
lambda =  5.645e-06; f = 20506056285305.6250000
lambda = 1.8817e-06; f = 2278444294915.3862305
lambda = 6.2723e-07; f = 253158342335.0020447
lambda = 2.0908e-07; f =  28127992679.7480698
lambda = 6.9692e-08; f =   3125094779.6249127
lambda = 2.3231e-08; f =    347153107.5155231
lambda = 7.7435e-09; f =     38545619.8999413
lambda = 2.5812e-09; f =      4273465.0460976

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1289031.3001830
lambda = -2.0908e-07; f =       142459.1488618
lambda = -6.9692e-08; f =        15168.1758285
lambda = -2.3231e-08; f =         1060.0452700
lambda = -7.7435e-09; f =         -495.7544954
lambda = -2.5812e-09; f =         -664.6977039
Norm of dx 8.0219e+11
Predicted improvement:        6.302636516
lambda =          1; f =         -684.2268550
lambda =    0.33333; f =         -684.3186619
lambda =    0.11111; f =         -684.3274410
lambda =   0.037037; f =         -684.3279549
lambda =   0.012346; f =         -680.0668275
lambda =  0.0041152; f =         -683.8894582
lambda =  0.0013717; f =         -684.2907739
lambda = 0.00045725; f =         -684.3276678
lambda = 0.00015242; f =         -684.3292051
Norm of dx     24.891
Predicted improvement:        0.009343389
lambda =          1; f =         -684.3387323
Norm of dx  0.0011632
Done for param e_a =   0.0988; f = -684.3387
Predicted improvement:        0.000534580
lambda =          1; f =         -684.3392642
Norm of dx  0.0005442
Done for param e_v =   0.1855; f = -684.3393
Predicted improvement:        0.000201181
lambda =          1; f =         -684.3394648
Norm of dx 7.3377e-05
Done for param e_g =   0.0409; f = -684.3395
Predicted improvement:        0.000335398
lambda =          1; f =         -684.3398015
Norm of dx 9.9423e-05
Done for param e_rer =   0.0433; f = -684.3398
Predicted improvement:        0.003651333
lambda =          1; f =         -684.3434653
Norm of dx 0.00067154
Done for param alp =   0.3372; f = -684.3435
Predicted improvement:        0.001942756
lambda =          1; f =         -684.3454167
Norm of dx 0.00032559
Done for param bet =   0.9130; f = -684.3454
Predicted improvement:        0.000550542
lambda =          1; f =         -684.3459673
Norm of dx 3.3128e-05
Done for param delt =   0.0999; f = -684.3460
Predicted improvement:        0.003879931
lambda =          1; f =         -684.3498433
Norm of dx  0.0052404
Done for param sig =   2.1350; f = -684.3498
Predicted improvement:        0.001898326
lambda =          1; f =         -684.3517425
Norm of dx   0.022081
Done for param phi2 =   5.4511; f = -684.3517
Predicted improvement:        0.035839712
lambda =          1; f =         -684.3868302
Norm of dx  0.0043374
Done for param hf =   0.6595; f = -684.3868
Predicted improvement:        0.000083710
lambda =          1; f =         -684.3869139
Norm of dx 0.00097354
Done for param rhoa =   0.4754; f = -684.3869
Predicted improvement:        0.008228872
lambda =          1; f =         -684.3952011
Norm of dx   0.011252
Done for param rhov =   0.2584; f = -684.3952
Predicted improvement:        0.000400311
lambda =          1; f =         -684.3956012
Norm of dx  0.0023442
Done for param rhog =   0.6585; f = -684.3956
Predicted improvement:        0.000012070
lambda =          1; f =         -684.3956132
Norm of dx 0.00051666
Done for param rhorer =   0.5477; f = -684.3956
Sequence of univariate steps!!
Actual dxnorm 0.028652
FVAL          -684.3956
Improvement   0.067657
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  8.754369e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.31748 s.
 
Iteration 17
Correct for low angle: 1.16383e-12
Predicted improvement: 33670989208.614326477
lambda =          1; f = 3655999329265310720.0000000
lambda =    0.33333; f = 406222147558699584.0000000
lambda =    0.11111; f = 45135794127373104.0000000
lambda =   0.037037; f = 5015088221102477.0000000
lambda =   0.012346; f = 557232019475772.5625000
lambda =  0.0041152; f = 61914667133185.5703125
lambda =  0.0013717; f = 6879406893024.9384766
lambda = 0.00045725; f = 764378354530.8298340
lambda = 0.00015242; f =  84930864835.6944275
lambda = 5.0805e-05; f =   9436741211.6665096
lambda = 1.6935e-05; f =   1048519219.1315014
lambda =  5.645e-06; f =    116499208.5074996
lambda = 1.8817e-06; f =     12942981.2870176
lambda = 6.2723e-07; f =      1437247.8290199
lambda = 2.0908e-07; f =       159002.1418699
lambda = 6.9692e-08; f =        17031.1949614
lambda = 2.3231e-08; f =         1275.4032167
lambda = 7.7435e-09; f =         -468.9977361
lambda = 2.5812e-09; f =         -660.9101780

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =  72204176520.2460785
lambda = -2.0908e-07; f =   8022305734.7163572
lambda = -6.9692e-08; f =    891240056.2785443
lambda = -2.3231e-08; f =     98983857.9183943
lambda = -7.7435e-09; f =     10983535.6263949
lambda = -2.5812e-09; f =      1215103.4023992
Norm of dx 4.2842e+11
Predicted improvement:        5.246689673
lambda =          1; f =         -684.2015457
lambda =    0.33333; f =         -684.3801333
lambda =    0.11111; f =         -684.3945376
lambda =   0.037037; f =         -684.3956082
lambda =   0.012346; f =         -684.1804349
lambda =  0.0041152; f =         -684.4004977
lambda =  0.0013717; f =         -684.4057523
lambda =  0.0026518; f =         -684.4075371
Norm of dx     7.5336
Predicted improvement:        0.005926054
lambda =          1; f =         -684.4135551
Norm of dx 0.00094231
Done for param e_a =   0.0999; f = -684.4136
Predicted improvement:        0.000290606
lambda =          1; f =         -684.4138447
Norm of dx 0.00040106
Done for param e_v =   0.1857; f = -684.4138
Predicted improvement:        0.000069290
lambda =          1; f =         -684.4139139
Norm of dx 4.2932e-05
Done for param e_g =   0.0408; f = -684.4139
Predicted improvement:        0.000123902
lambda =          1; f =         -684.4140381
Norm of dx 6.0831e-05
Done for param e_rer =   0.0435; f = -684.4140
Predicted improvement:        0.004125129
lambda =          1; f =         -684.4181780
Norm of dx 0.00071824
Done for param alp =   0.3383; f = -684.4182
Predicted improvement:        0.000613292
lambda =          1; f =         -684.4187928
Norm of dx 0.00018518
Done for param bet =   0.9117; f = -684.4188
Predicted improvement:        0.010020172
lambda =          1; f =         -684.4288129
Norm of dx 0.00014133
Done for param delt =   0.0999; f = -684.4288
Predicted improvement:        0.001814777
lambda =          1; f =         -684.4306269
Norm of dx  0.0035565
Done for param sig =   2.1289; f = -684.4306
Predicted improvement:        0.000268903
lambda =          1; f =         -684.4308960
Norm of dx   0.001567
Done for param phi1 =   1.3954; f = -684.4309
Predicted improvement:        0.000775407
lambda =          1; f =         -684.4316716
Norm of dx   0.014172
Done for param phi2 =   5.4849; f = -684.4317
Predicted improvement:        0.023397238
lambda =          1; f =         -684.4546740
Norm of dx  0.0034403
Done for param hf =   0.6641; f = -684.4547
Predicted improvement:        0.000024598
lambda =          1; f =         -684.4546986
Norm of dx 0.00052828
Done for param rhoa =   0.4744; f = -684.4547
Predicted improvement:        0.005273350
lambda =          1; f =         -684.4599972
Norm of dx  0.0090088
Done for param rhov =   0.2494; f = -684.4600
Predicted improvement:        0.000416921
lambda =          1; f =         -684.4604139
Norm of dx  0.0023876
Done for param rhog =   0.6611; f = -684.4604
Predicted improvement:        0.000027709
lambda =          1; f =         -684.4604416
Norm of dx 0.00078473
Done for param rhorer =   0.5465; f = -684.4604
Sequence of univariate steps!!
Actual dxnorm 0.035997
FVAL          -684.4604
Improvement   0.064828
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.018327e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.37293 s.
 
Iteration 18
Correct for low angle: 2.58097e-12
Predicted improvement: 11830376840.648723602
lambda =          1; f = 45972429638090356686848.0000000
lambda =    0.33333; f = 5108047737262422622208.0000000
lambda =    0.11111; f = 567560859594766745600.0000000
lambda =   0.037037; f = 63062317699065954304.0000000
lambda =   0.012346; f = 7006924177556462592.0000000
lambda =  0.0041152; f = 778547127096726784.0000000
lambda =  0.0013717; f = 86505235096453632.0000000
lambda = 0.00045725; f = 9611692372618732.0000000
lambda = 0.00015242; f = 1067965680554094.7500000
lambda = 5.0805e-05; f = 118662807185917.7812500
lambda = 1.6935e-05; f = 13184740950603.4843750
lambda =  5.645e-06; f = 1464966081877.7670898
lambda = 1.8817e-06; f = 162772297085.3853149
lambda = 6.2723e-07; f =  18085239719.1390495
lambda = 2.0908e-07; f =   2009280324.8015687
lambda = 6.9692e-08; f =    223189385.2980371
lambda = 2.3231e-08; f =     24777093.4482415
lambda = 7.7435e-09; f =      2745368.8393148
lambda = 2.5812e-09; f =       302094.3239444

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =        82659.4871190
lambda = -2.0908e-07; f =         8524.9684534
lambda = -6.9692e-08; f =          322.2418300
lambda = -2.3231e-08; f =         -577.6915336
lambda = -7.7435e-09; f =         -673.8572276
lambda = -2.5812e-09; f =         -683.4456607
Norm of dx 2.1441e+11
Predicted improvement:        5.685591349
lambda =          1; f =         -684.2591742
lambda =    0.33333; f =         -684.4419838
lambda =    0.11111; f =         -684.4587718
lambda =   0.037037; f =         -684.4603519
lambda =   0.012346; f =         -666.2377940
lambda =  0.0041152; f =         -682.4689505
lambda =  0.0013717; f =         -684.2496245
lambda = 0.00045725; f =         -684.4404858
lambda = 0.00015242; f =         -684.4593798
lambda = 5.0805e-05; f =         -684.4607088
Norm of dx     39.771
Predicted improvement:        0.002965974
lambda =          1; f =         -684.4637077
Norm of dx 0.00067571
Done for param e_a =   0.1006; f = -684.4637
Predicted improvement:        0.000325689
lambda =          1; f =         -684.4640321
Norm of dx  0.0004239
Done for param e_v =   0.1854; f = -684.4640
Predicted improvement:        0.000218852
lambda =          1; f =         -684.4642503
Norm of dx 7.6313e-05
Done for param e_g =   0.0408; f = -684.4643
Predicted improvement:        0.001547600
lambda =          1; f =         -684.4658013
Norm of dx 0.00044131
Done for param alp =   0.3379; f = -684.4658
Predicted improvement:        0.000817037
lambda =          1; f =         -684.4666207
Norm of dx 0.00021449
Done for param bet =   0.9115; f = -684.4666
Predicted improvement:        0.000270175
lambda =          1; f =         -684.4668909
Norm of dx 2.3206e-05
Done for param delt =   0.0999; f = -684.4669
Predicted improvement:        0.001906190
lambda =          1; f =         -684.4687960
Norm of dx  0.0036272
Done for param sig =   2.1259; f = -684.4688
Predicted improvement:        0.000111476
lambda =          1; f =         -684.4689075
Norm of dx   0.001007
Done for param phi1 =   1.3975; f = -684.4689
Predicted improvement:        0.000635823
lambda =          1; f =         -684.4695435
Norm of dx   0.012852
Done for param phi2 =   5.4994; f = -684.4695
Predicted improvement:        0.015205338
lambda =          1; f =         -684.4845430
Norm of dx  0.0027386
Done for param hf =   0.6669; f = -684.4845
Predicted improvement:        0.000024841
lambda =          1; f =         -684.4845678
Norm of dx 0.00053025
Done for param rhoa =   0.4739; f = -684.4846
Predicted improvement:        0.003579000
lambda =          1; f =         -684.4881587
Norm of dx  0.0074102
Done for param rhov =   0.2420; f = -684.4882
Predicted improvement:        0.000166053
lambda =          1; f =         -684.4883247
Norm of dx  0.0015038
Done for param rhog =   0.6626; f = -684.4883
Sequence of univariate steps!!
Actual dxnorm 0.016992
FVAL          -684.4883
Improvement   0.027883
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.229424e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.37332 s.
 
Iteration 19
Near-singular H problem.
Correct for low angle: 4.98442e-22
Predicted improvement: 186955208664.302551270
lambda =          1; f = 385691285985087455232.0000000
lambda =    0.33333; f = 42854587330171166720.0000000
lambda =    0.11111; f = 4761620813961739264.0000000
lambda =   0.037037; f = 529068979161839168.0000000
lambda =   0.012346; f = 58785442073345256.0000000
lambda =  0.0041152; f = 6531715767344186.0000000
lambda =  0.0013717; f = 725746190176823.1250000
lambda = 0.00045725; f = 80638463509885.6406250
lambda = 0.00015242; f = 8959828590038.0019531
lambda = 5.0805e-05; f = 995536279992.2979736
lambda = 1.6935e-05; f = 110615065151.5276184
lambda =  5.645e-06; f =  12290536705.4705963
lambda = 1.8817e-06; f =   1365606093.8224947
lambda = 6.2723e-07; f =    151730579.0816944
lambda = 2.0908e-07; f =     16857409.9928417
lambda = 6.9692e-08; f =      1872130.3436887
lambda = 2.3231e-08; f =       207304.6004330
lambda = 7.7435e-09; f =        22392.1288797
lambda = 2.5812e-09; f =         1868.9967824

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     37737452.7141310
lambda = -2.0908e-07; f =      4191371.9150978
lambda = -6.9692e-08; f =       464744.6298066
lambda = -2.3231e-08; f =        50912.1348177
lambda = -7.7435e-09; f =         5009.6678947
lambda = -2.5812e-09; f =          -64.2990716
Norm of dx 2.1946e+10
Predicted improvement:        1.991004997
lambda =          1; f =         -684.3844838
lambda =    0.33333; f =         -684.4811530
lambda =    0.11111; f =         -684.4877449
lambda =   0.037037; f =         -684.4883096
lambda =   0.012346; f =         -676.7002494
lambda =  0.0041152; f =         -683.6343792
lambda =  0.0013717; f =         -684.3970979
lambda = 0.00045725; f =         -684.4794027
lambda = 0.00015242; f =         -684.4877380
lambda = 5.0805e-05; f =         -684.4883943
Norm of dx      22.38
Predicted improvement:        0.001962736
lambda =          1; f =         -684.4903749
Norm of dx 0.00055435
Done for param e_a =   0.1011; f = -684.4904
Predicted improvement:        0.000149409
lambda =          1; f =         -684.4905239
Norm of dx  0.0002862
Done for param e_v =   0.1851; f = -684.4905
Predicted improvement:        0.000096905
lambda =          1; f =         -684.4906206
Norm of dx 5.0639e-05
Done for param e_g =   0.0407; f = -684.4906
Predicted improvement:        0.000464568
lambda =          1; f =         -684.4910857
Norm of dx  0.0002424
Done for param alp =   0.3377; f = -684.4911
Predicted improvement:        0.000915000
lambda =          1; f =         -684.4920035
Norm of dx 0.00022775
Done for param bet =   0.9113; f = -684.4920
Predicted improvement:        0.000120991
lambda =          1; f =         -684.4921245
Norm of dx 1.5529e-05
Done for param delt =   0.0999; f = -684.4921
Predicted improvement:        0.001497580
lambda =          1; f =         -684.4936214
Norm of dx  0.0032013
Done for param sig =   2.1231; f = -684.4936
Predicted improvement:        0.000079181
lambda =          1; f =         -684.4937006
Norm of dx   0.000847
Done for param phi1 =   1.3991; f = -684.4937
Predicted improvement:        0.000557880
lambda =          1; f =         -684.4942586
Norm of dx   0.012055
Done for param phi2 =   5.5122; f = -684.4943
Predicted improvement:        0.009955523
lambda =          1; f =         -684.5041056
Norm of dx  0.0021937
Done for param hf =   0.6691; f = -684.5041
Predicted improvement:        0.000040256
lambda =          1; f =         -684.5041459
Norm of dx 0.00067469
Done for param rhoa =   0.4733; f = -684.5041
Predicted improvement:        0.002154940
lambda =          1; f =         -684.5063054
Norm of dx    0.00574
Done for param rhov =   0.2363; f = -684.5063
Predicted improvement:        0.000103081
lambda =          1; f =         -684.5064085
Norm of dx  0.0011834
Done for param rhog =   0.6638; f = -684.5064
Sequence of univariate steps!!
Actual dxnorm 0.01464
FVAL          -684.5064
Improvement   0.018084
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.198455e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.35357 s.
 
Iteration 20
Correct for low angle: 1.73781e-12
Predicted improvement: 28294712883.794605255
lambda =          1; f = 759951711309236501741568.0000000
lambda =    0.33333; f = 84439079033126978060288.0000000
lambda =    0.11111; f = 9382119892158801510400.0000000
lambda =   0.037037; f = 1042457765658466320384.0000000
lambda =   0.012346; f = 115828640583066550272.0000000
lambda =  0.0041152; f = 12869848938456737792.0000000
lambda =  0.0013717; f = 1429983210311641856.0000000
lambda = 0.00045725; f = 158887021677146496.0000000
lambda = 0.00015242; f = 17654112956077968.0000000
lambda = 5.0805e-05; f = 1961567918362167.7500000
lambda = 1.6935e-05; f = 217951928305830.5625000
lambda =  5.645e-06; f = 24216860048043.5742188
lambda = 1.8817e-06; f = 2690755268891.4741211
lambda = 6.2723e-07; f = 298970487704.8591919
lambda = 2.0908e-07; f =  33218169363.9189987
lambda = 6.9692e-08; f =   3690649403.2031980
lambda = 2.3231e-08; f =    409985655.4878996
lambda = 7.7435e-09; f =     45524729.1139602
lambda = 2.5812e-09; f =      5048159.8791781

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1561629.5210860
lambda = -2.0908e-07; f =       172687.2793778
lambda = -6.9692e-08; f =        18507.1288561
lambda = -2.3231e-08; f =         1424.3772740
lambda = -7.7435e-09; f =         -457.5840884
lambda = -2.5812e-09; f =         -661.3168576
Norm of dx 8.7175e+11
Predicted improvement:        2.251251890
lambda =          1; f =         -684.3873431
lambda =    0.33333; f =         -684.4987344
lambda =    0.11111; f =         -684.5057824
lambda =   0.037037; f =         -684.5063909
lambda =   0.012346; f =         -676.1042632
lambda =  0.0041152; f =         -683.5857420
lambda =  0.0013717; f =         -684.4082468
lambda = 0.00045725; f =         -684.4968747
lambda = 0.00015242; f =         -684.5058067
lambda = 5.0805e-05; f =         -684.5064941
Norm of dx     23.457
Predicted improvement:        0.001215111
lambda =          1; f =         -684.5077179
Norm of dx 0.00043928
Done for param e_a =   0.1015; f = -684.5077
Predicted improvement:        0.000055470
lambda =          1; f =         -684.5077733
Norm of dx   0.000174
Done for param e_v =   0.1850; f = -684.5078
Predicted improvement:        0.000065190
lambda =          1; f =         -684.5078384
Norm of dx 4.1469e-05
Done for param e_g =   0.0407; f = -684.5078
Predicted improvement:        0.000070803
lambda =          1; f =         -684.5079092
Norm of dx 9.4829e-05
Done for param alp =   0.3377; f = -684.5079
Predicted improvement:        0.000906317
lambda =          1; f =         -684.5088182
Norm of dx  0.0002273
Done for param bet =   0.9111; f = -684.5088
Predicted improvement:        0.000120907
lambda =          1; f =         -684.5089391
Norm of dx 1.5523e-05
Done for param delt =   0.0999; f = -684.5089
Predicted improvement:        0.001152106
lambda =          1; f =         -684.5100908
Norm of dx  0.0027983
Done for param sig =   2.1207; f = -684.5101
Predicted improvement:        0.000050413
lambda =          1; f =         -684.5101412
Norm of dx 0.00067492
Done for param phi1 =   1.4005; f = -684.5101
Predicted improvement:        0.000389336
lambda =          1; f =         -684.5105306
Norm of dx   0.010082
Done for param phi2 =   5.5230; f = -684.5105
Predicted improvement:        0.006443351
lambda =          1; f =         -684.5169177
Norm of dx  0.0017505
Done for param hf =   0.6708; f = -684.5169
Predicted improvement:        0.000027900
lambda =          1; f =         -684.5169456
Norm of dx 0.00056159
Done for param rhoa =   0.4727; f = -684.5169
Predicted improvement:        0.001234015
lambda =          1; f =         -684.5181813
Norm of dx  0.0043359
Done for param rhov =   0.2319; f = -684.5182
Predicted improvement:        0.000062716
lambda =          1; f =         -684.5182440
Norm of dx  0.0009221
Done for param rhog =   0.6647; f = -684.5182
Sequence of univariate steps!!
Actual dxnorm 0.012203
FVAL          -684.5182
Improvement   0.011835
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.845592e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.37415 s.
 
Iteration 21
Near-singular H problem.
Correct for low angle: 1.99696e-21
Predicted improvement: 33405975097.640480042
lambda =          1; f = 36202803311109025792.0000000
lambda =    0.33333; f = 4022533700822191104.0000000
lambda =    0.11111; f = 446948188842861120.0000000
lambda =   0.037037; f = 49660909825634576.0000000
lambda =   0.012346; f = 5517878854249745.0000000
lambda =  0.0041152; f = 613097645383397.8750000
lambda =  0.0013717; f = 68121958901493.7812500
lambda = 0.00045725; f = 7569105978657.5927734
lambda = 0.00015242; f = 841011586356.4550781
lambda = 5.0805e-05; f =  93445668401.7330780
lambda = 1.6935e-05; f =  10382830507.0837364
lambda =  5.645e-06; f =   1153640255.7321124
lambda = 1.8817e-06; f =    128179325.2429609
lambda = 6.2723e-07; f =     14240772.7550235
lambda = 2.0908e-07; f =      1581447.7867756
lambda = 6.9692e-08; f =       175024.5975416
lambda = 2.3231e-08; f =        18811.4403272
lambda = 7.7435e-09; f =         1473.1004209
lambda = 2.5812e-09; f =         -447.1564180

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      3860859.5948763
lambda = -2.0908e-07; f =       428011.1765137
lambda = -6.9692e-08; f =        46828.6216626
lambda = -2.3231e-08; f =         4555.7287974
lambda = -7.7435e-09; f =         -114.8094536
lambda = -2.5812e-09; f =         -624.9424407
Norm of dx  6.784e+09
Predicted improvement:        2.245337740
lambda =          1; f =         -684.4004213
lambda =    0.33333; f =         -684.5109711
lambda =    0.11111; f =         -684.5176630
lambda =   0.037037; f =         -684.5182289
lambda =   0.012346; f =         -676.4963908
lambda =  0.0041152; f =         -683.6397839
lambda =  0.0013717; f =         -684.4247608
lambda = 0.00045725; f =         -684.5092265
lambda = 0.00015242; f =         -684.5176984
lambda = 5.0805e-05; f =         -684.5183354
Norm of dx     23.169
Predicted improvement:        0.000710277
lambda =          1; f =         -684.5190496
Norm of dx 0.00033777
Done for param e_a =   0.1019; f = -684.5190
Predicted improvement:        0.000017455
lambda =          1; f =         -684.5190671
Norm of dx 9.7473e-05
Done for param e_v =   0.1849; f = -684.5191
Predicted improvement:        0.000039382
lambda =          1; f =         -684.5191064
Norm of dx 3.2188e-05
Done for param e_g =   0.0406; f = -684.5191
Predicted improvement:        0.000798077
lambda =          1; f =         -684.5199067
Norm of dx 0.00021382
Done for param bet =   0.9108; f = -684.5199
Predicted improvement:        0.000109977
lambda =          1; f =         -684.5200167
Norm of dx 1.4805e-05
Done for param delt =   0.0999; f = -684.5200
Predicted improvement:        0.000873933
lambda =          1; f =         -684.5208903
Norm of dx  0.0024306
Done for param sig =   2.1188; f = -684.5209
Predicted improvement:        0.000029697
lambda =          1; f =         -684.5209201
Norm of dx 0.00051744
Done for param phi1 =   1.4018; f = -684.5209
Predicted improvement:        0.000249953
lambda =          1; f =         -684.5211700
Norm of dx  0.0080868
Done for param phi2 =   5.5319; f = -684.5212
Predicted improvement:        0.004104824
lambda =          1; f =         -684.5252463
Norm of dx  0.0013881
Done for param hf =   0.6722; f = -684.5252
Predicted improvement:        0.000015126
lambda =          1; f =         -684.5252614
Norm of dx 0.00041348
Done for param rhoa =   0.4723; f = -684.5253
Predicted improvement:        0.000687310
lambda =          1; f =         -684.5259493
Norm of dx  0.0032308
Done for param rhov =   0.2287; f = -684.5259
Predicted improvement:        0.000037130
lambda =          1; f =         -684.5259865
Norm of dx 0.00070893
Done for param rhog =   0.6654; f = -684.5260
Sequence of univariate steps!!
Actual dxnorm 0.0098566
FVAL          -684.526
Improvement   0.0077425
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  6.348912e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.38486 s.
 
Iteration 22
Near-singular H problem.
Correct for low angle: 3.12112e-21
Predicted improvement: 19547036351.711292267
lambda =          1; f = 20675223922814910464.0000000
lambda =    0.33333; f = 2297247102211610368.0000000
lambda =    0.11111; f = 255249677915718688.0000000
lambda =   0.037037; f = 28361075288037160.0000000
lambda =   0.012346; f = 3151230575582089.5000000
lambda =  0.0041152; f = 350136726627301.6250000
lambda =  0.0013717; f = 38904079404991.0468750
lambda = 0.00045725; f = 4322675045252.5332031
lambda = 0.00015242; f = 480297078787.6662598
lambda = 5.0805e-05; f =  53366292201.0030212
lambda = 1.6935e-05; f =   5929570994.4418335
lambda =  5.645e-06; f =    658835146.4106845
lambda = 1.8817e-06; f =     73201480.8527456
lambda = 6.2723e-07; f =      8132290.5200168
lambda = 2.0908e-07; f =       902781.8477769
lambda = 6.9692e-08; f =        99635.3086372
lambda = 2.3231e-08; f =        10440.8504209
lambda = 7.7435e-09; f =          545.0270672
lambda = 2.5812e-09; f =         -549.6257002

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2571436.5124636
lambda = -2.0908e-07; f =       284791.2153256
lambda = -6.9692e-08; f =        30931.7134061
lambda = -2.3231e-08; f =         2795.0807460
lambda = -7.7435e-09; f =         -308.5400358
lambda = -2.5812e-09; f =         -645.8383672
Norm of dx  5.217e+09
Predicted improvement:        0.546132566
lambda =          1; f =         -684.4835241
lambda =    0.33333; f =         -684.5218216
lambda =    0.11111; f =         -684.5256851
lambda =   0.037037; f =         -684.5259838
lambda =   0.012346; f =         -680.5661536
lambda =  0.0041152; f =         -684.0890682
lambda =  0.0013717; f =         -684.4784409
lambda = 0.00045725; f =         -684.5210366
lambda = 0.00015242; f =         -684.5255475
lambda = 5.0805e-05; f =         -684.5259747
lambda = 1.6935e-05; f =         -684.5259975
Norm of dx     12.236
Predicted improvement:        0.000403145
lambda =          1; f =         -684.5264023
Norm of dx 0.00025562
Done for param e_a =   0.1021; f = -684.5264
Predicted improvement:        0.000022816
lambda =          1; f =         -684.5264251
Norm of dx 2.4474e-05
Done for param e_g =   0.0406; f = -684.5264
Predicted improvement:        0.000056124
lambda =          1; f =         -684.5264812
Norm of dx 8.4685e-05
Done for param alp =   0.3378; f = -684.5265
Predicted improvement:        0.000730456
lambda =          1; f =         -684.5272136
Norm of dx 0.00020496
Done for param bet =   0.9106; f = -684.5272
Predicted improvement:        0.000563730
lambda =          1; f =         -684.5277772
Norm of dx  0.0019475
Done for param sig =   2.1169; f = -684.5278
Predicted improvement:        0.000061518
lambda =          1; f =         -684.5278388
Norm of dx 0.00074389
Done for param phi1 =   1.4027; f = -684.5278
Predicted improvement:        0.000206336
lambda =          1; f =         -684.5280451
Norm of dx  0.0073538
Done for param phi2 =   5.5394; f = -684.5280
Predicted improvement:        0.002703485
lambda =          1; f =         -684.5307334
Norm of dx  0.0011208
Done for param hf =   0.6733; f = -684.5307
Predicted improvement:        0.000323967
lambda =          1; f =         -684.5310575
Norm of dx  0.0022156
Done for param rhov =   0.2265; f = -684.5311
Predicted improvement:        0.000023375
lambda =          1; f =         -684.5310809
Norm of dx 0.00056214
Done for param rhog =   0.6660; f = -684.5311
Predicted improvement:        0.000011334
lambda =          1; f =         -684.5310922
Norm of dx 0.00050226
Done for param rhorer =   0.5470; f = -684.5311
Sequence of univariate steps!!
Actual dxnorm 0.0082139
FVAL          -684.5311
Improvement   0.0051057
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.477039e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.46671 s.
 
Iteration 23
Correct for low angle: 1.00879e-11
Predicted improvement: 1556827244.417407036
lambda =          1; f = 97285902504240896.0000000
lambda =    0.33333; f = 10809544699656936.0000000
lambda =    0.11111; f = 1201060514504870.7500000
lambda =   0.037037; f = 133451165718175.7187500
lambda =   0.012346; f = 14827906448239.4687500
lambda =  0.0041152; f = 1647544875923.1928711
lambda =  0.0013717; f = 183060446372.8547974
lambda = 0.00045725; f =  20340017399.2334290
lambda = 0.00015242; f =   2259990801.7105174
lambda = 5.0805e-05; f =    251105979.6122378
lambda = 1.6935e-05; f =     27898895.4572186
lambda =  5.645e-06; f =      3098888.0139497
lambda = 1.8817e-06; f =       343586.7366570
lambda = 6.2723e-07; f =        37526.4518495
lambda = 2.0908e-07; f =         3547.8312372
lambda = 6.9692e-08; f =         -218.2137366
lambda = 2.3231e-08; f =         -633.5817933
lambda = 7.7435e-09; f =         -678.9541565
lambda = 2.5812e-09; f =         -683.9331543

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =   3055144612.7764349
lambda = -2.0908e-07; f =    339381750.6579183
lambda = -6.9692e-08; f =     37682430.2544327
lambda = -2.3231e-08; f =      4177653.1165323
lambda = -7.7435e-09; f =       460689.7813657
lambda = -2.5812e-09; f =        49623.4971102
Norm of dx 8.8129e+10
Predicted improvement:        0.653319864
lambda =          1; f =         -684.5136707
lambda =    0.33333; f =         -684.5297303
lambda =    0.11111; f =         -684.5310651
lambda =   0.037037; f =         -684.4171271
lambda =   0.012346; f =         -684.5291918
lambda =  0.0041152; f =         -684.5344661
Norm of dx     1.8942
Predicted improvement:        0.000201799
lambda =          1; f =         -684.5346685
Norm of dx 0.00018097
Done for param e_a =   0.1020; f = -684.5347
Predicted improvement:        0.000050295
lambda =          1; f =         -684.5347187
Norm of dx  3.635e-05
Done for param e_g =   0.0406; f = -684.5347
Predicted improvement:        0.000025144
lambda =          1; f =         -684.5347438
Norm of dx 2.7475e-05
Done for param e_rer =   0.0436; f = -684.5347
Predicted improvement:        0.000030033
lambda =          1; f =         -684.5347739
Norm of dx 6.2036e-05
Done for param alp =   0.3389; f = -684.5348
Predicted improvement:        0.000085007
lambda =          1; f =         -684.5348590
Norm of dx 7.0205e-05
Done for param bet =   0.9100; f = -684.5349
Predicted improvement:        0.000363819
lambda =          1; f =         -684.5352227
Norm of dx  0.0015624
Done for param sig =   2.1150; f = -684.5352
Predicted improvement:        0.000018530
lambda =          1; f =         -684.5352412
Norm of dx 0.00040832
Done for param phi1 =   1.4044; f = -684.5352
Predicted improvement:        0.000275802
lambda =          1; f =         -684.5355171
Norm of dx  0.0085033
Done for param phi2 =   5.5404; f = -684.5355
Predicted improvement:        0.001451359
lambda =          1; f =         -684.5369625
Norm of dx 0.00081798
Done for param hf =   0.6740; f = -684.5370
Predicted improvement:        0.000024369
lambda =          1; f =         -684.5369868
Norm of dx 0.00052451
Done for param rhoa =   0.4718; f = -684.5370
Predicted improvement:        0.000169582
lambda =          1; f =         -684.5371565
Norm of dx   0.001601
Done for param rhov =   0.2252; f = -684.5372
Sequence of univariate steps!!
Actual dxnorm 0.0033892
FVAL          -684.5372
Improvement   0.0060643
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  1.551493e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.37187 s.
 
Iteration 24
Correct for low angle: 3.94528e-12
Predicted improvement: 6351572851.082464218
lambda =          1; f = 184503424471083165679616.0000000
lambda =    0.33333; f = 20500380496179721404416.0000000
lambda =    0.11111; f = 2277820054928643063808.0000000
lambda =   0.037037; f = 253091117146815135744.0000000
lambda =   0.012346; f = 28121235216042156032.0000000
lambda =  0.0041152; f = 3124581683173725696.0000000
lambda =  0.0013717; f = 347175740075650432.0000000
lambda = 0.00045725; f = 38575081397558024.0000000
lambda = 0.00015242; f = 4286119877593909.5000000
lambda = 5.0805e-05; f = 476235449391046.3125000
lambda = 1.6935e-05; f = 52915019077333.7031250
lambda =  5.645e-06; f = 5879436278748.0966797
lambda = 1.8817e-06; f = 653267268772.9501953
lambda = 6.2723e-07; f =  72584108731.5884705
lambda = 2.0908e-07; f =   8064519452.9131451
lambda = 6.9692e-08; f =    895930145.3917550
lambda = 2.3231e-08; f =     99504870.8887427
lambda = 7.7435e-09; f =     11041389.8779758
lambda = 2.5812e-09; f =      1221519.4655054

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      1119037.2322685
lambda = -2.0908e-07; f =       123643.5304781
lambda = -6.9692e-08; f =        13101.9363000
lambda = -2.3231e-08; f =          838.7283857
lambda = -7.7435e-09; f =         -517.6536860
lambda = -2.5812e-09; f =         -666.4357285
Norm of dx 4.2954e+11
Predicted improvement:        0.240631254
lambda =          1; f =         -684.5278820
lambda =    0.33333; f =         -684.5369722
lambda =    0.11111; f =         -683.6806338
lambda =   0.037037; f =         -684.4538839
lambda =   0.012346; f =         -684.5318651
lambda =  0.0041152; f =         -684.5378889
Norm of dx      1.007
Predicted improvement:        0.000205615
lambda =          1; f =         -684.5380951
Norm of dx 0.00018304
Done for param e_a =   0.1022; f = -684.5381
Predicted improvement:        0.000084865
lambda =          1; f =         -684.5381800
Norm of dx 0.00010437
Done for param alp =   0.3394; f = -684.5382
Predicted improvement:        0.000010012
lambda =          1; f =         -684.5381900
Norm of dx 4.4668e-06
Done for param delt =   0.0999; f = -684.5382
Predicted improvement:        0.000672067
lambda =          1; f =         -684.5388629
Norm of dx  0.0024542
Done for param phi1 =   1.4047; f = -684.5389
Predicted improvement:        0.000120885
lambda =          1; f =         -684.5389838
Norm of dx  0.0056337
Done for param phi2 =   5.5464; f = -684.5390
Predicted improvement:        0.000859856
lambda =          1; f =         -684.5398409
Norm of dx 0.00062711
Done for param hf =   0.6750; f = -684.5398
Predicted improvement:        0.000173600
lambda =          1; f =         -684.5400145
Norm of dx  0.0016174
Done for param rhov =   0.2237; f = -684.5400
Predicted improvement:        0.000030054
lambda =          1; f =         -684.5400446
Norm of dx 0.00063703
Done for param rhog =   0.6666; f = -684.5400
Sequence of univariate steps!!
Actual dxnorm 0.0072515
FVAL          -684.54
Improvement   0.0028881
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  5.948241e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.3088 s.
 
Iteration 25
Correct for low angle: 1.08444e-11
Predicted improvement: 1722828100.435850382
lambda =          1; f = 940966730086535808.0000000
lambda =    0.33333; f = 104551858835706496.0000000
lambda =    0.11111; f = 11616873183034514.0000000
lambda =   0.037037; f = 1290763680025811.5000000
lambda =   0.012346; f = 143418184343129.2187500
lambda =  0.0041152; f = 15935353040037.2578125
lambda =  0.0013717; f = 1770594523206.8381348
lambda = 0.00045725; f = 196732638063.3889160
lambda = 0.00015242; f =  21859152697.0571365
lambda = 5.0805e-05; f =   2428784576.5549808
lambda = 1.6935e-05; f =    269861165.9913740
lambda =  5.645e-06; f =     29982913.8868664
lambda = 1.8817e-06; f =      3330483.7131447
lambda = 6.2723e-07; f =       369335.0809609
lambda = 2.0908e-07; f =        40392.6339771
lambda = 6.9692e-08; f =         3868.0424433
lambda = 2.3231e-08; f =         -182.0706712
lambda = 7.7435e-09; f =         -629.5296737
lambda = 2.5812e-09; f =         -678.6712327

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =  18764315352.8280945
lambda = -2.0908e-07; f =   2084729608.0639744
lambda = -6.9692e-08; f =    231571450.5866283
lambda = -2.3231e-08; f =     25708037.8101822
lambda = -7.7435e-09; f =      2848675.0012931
lambda = -2.5812e-09; f =       313528.9677975
Norm of dx  2.184e+11
Predicted improvement:        0.023465386
lambda =          1; f =         -684.5400357
lambda =    0.33333; f =         -679.6935976
lambda =    0.11111; f =         -684.0050715
lambda =   0.037037; f =         -684.4817631
lambda =   0.012346; f =         -684.5339552
lambda =  0.0041152; f =         -684.5394968
lambda =  0.0013717; f =         -684.5400266
lambda = 0.00045725; f =         -684.5400569
Norm of dx    0.17686
Predicted improvement:        0.000058339
lambda =          1; f =         -684.5401153
Norm of dx 9.7793e-05
Done for param e_a =   0.1023; f = -684.5401
Predicted improvement:        0.000018483
lambda =          1; f =         -684.5401338
Norm of dx 0.00010009
Done for param e_v =   0.1850; f = -684.5401
Predicted improvement:        0.000013855
lambda =          1; f =         -684.5401477
Norm of dx 2.0458e-05
Done for param e_rer =   0.0436; f = -684.5401
Predicted improvement:        0.000024229
lambda =          1; f =         -684.5401719
Norm of dx 5.5781e-05
Done for param alp =   0.3393; f = -684.5402
Predicted improvement:        0.000014052
lambda =          1; f =         -684.5401859
Norm of dx 0.00030593
Done for param sig =   2.1113; f = -684.5402
Predicted improvement:        0.000180538
lambda =          1; f =         -684.5403666
Norm of dx  0.0012724
Done for param phi1 =   1.4061; f = -684.5404
Predicted improvement:        0.000040268
lambda =          1; f =         -684.5404069
Norm of dx  0.0032531
Done for param phi2 =   5.5496; f = -684.5404
Predicted improvement:        0.000446463
lambda =          1; f =         -684.5408523
Norm of dx 0.00045075
Done for param hf =   0.6755; f = -684.5409
Predicted improvement:        0.000043270
lambda =          1; f =         -684.5408956
Norm of dx  0.0008074
Done for param rhov =   0.2228; f = -684.5409
Sequence of univariate steps!!
Actual dxnorm 0.0036205
FVAL          -684.5409
Improvement   0.00085099
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.509825e-24.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.29434 s.
 
Iteration 26
Correct for low angle: 6.82444e-12
Predicted improvement: 3457098767.533501148
lambda =          1; f = 376396616579991040.0000000
lambda =    0.33333; f = 41821846250912648.0000000
lambda =    0.11111; f = 4646871793738893.0000000
lambda =   0.037037; f = 516319084220123.3125000
lambda =   0.012346; f = 57368785810809.1093750
lambda =  0.0041152; f = 6374309092549.8486328
lambda =  0.0013717; f = 708256418112.9249268
lambda = 0.00045725; f =  78695107928.3389130
lambda = 0.00015242; f =   8743883936.5570335
lambda = 5.0805e-05; f =    971536613.7127291
lambda = 1.6935e-05; f =    107946099.5363822
lambda =  5.645e-06; f =     11992808.8827293
lambda = 1.8817e-06; f =      1331732.2399496
lambda = 6.2723e-07; f =       147298.1354541
lambda = 2.0908e-07; f =        15737.2516091
lambda = 6.9692e-08; f =         1133.6692987
lambda = 2.3231e-08; f =         -484.2534964
lambda = 7.7435e-09; f =         -662.6642400
lambda = 2.5812e-09; f =         -682.2181941

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =  29442435623.5153275
lambda = -2.0908e-07; f =   3271138535.7151370
lambda = -6.9692e-08; f =    363378371.5106769
lambda = -2.3231e-08; f =     40347820.1634609
lambda = -7.7435e-09; f =      4473507.1035231
lambda = -2.5812e-09; f =       493462.1239840
Norm of dx 2.7357e+11
Predicted improvement:        0.184964837
lambda =          1; f =         -678.9347495
lambda =    0.33333; f =         -684.5407484
lambda =    0.11111; f =         -679.5685209
lambda =   0.037037; f =         -683.9976824
lambda =   0.012346; f =         -684.4835879
lambda =  0.0041152; f =         -684.5355430
lambda =  0.0013717; f =         -684.5406391
lambda = 0.00045725; f =         -684.5409798
Norm of dx     5.4871
Predicted improvement:        0.000035788
lambda =          1; f =         -684.5410157
Norm of dx 7.6693e-05
Done for param e_a =   0.1024; f = -684.5410
Predicted improvement:        0.000013116
lambda =          1; f =         -684.5410288
Norm of dx 1.8533e-05
Done for param e_g =   0.0406; f = -684.5410
Predicted improvement:        0.000010313
lambda =          1; f =         -684.5410391
Norm of dx 3.6397e-05
Done for param alp =   0.3393; f = -684.5410
Predicted improvement:        0.000011354
lambda =          1; f =         -684.5410504
Norm of dx 2.5731e-05
Done for param bet =   0.9097; f = -684.5411
Predicted improvement:        0.000011136
lambda =          1; f =         -684.5410616
Norm of dx  4.711e-06
Done for param delt =   0.0999; f = -684.5411
Predicted improvement:        0.000029072
lambda =          1; f =         -684.5410907
Norm of dx 0.00043993
Done for param sig =   2.1116; f = -684.5411
Predicted improvement:        0.000155504
lambda =          1; f =         -684.5412460
Norm of dx 0.00026544
Done for param hf =   0.6757; f = -684.5412
Predicted improvement:        0.000023092
lambda =          1; f =         -684.5412690
Norm of dx 0.00058968
Done for param rhov =   0.2222; f = -684.5413
Sequence of univariate steps!!
Actual dxnorm 0.0025111
FVAL          -684.5413
Improvement   0.00037346
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.177304e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.24323 s.
 
Iteration 27
Near-singular H problem.
Correct for low angle: 1.28003e-20
Predicted improvement: 7011732781.391575813
lambda =          1; f = 76865694540300812288.0000000
lambda =    0.33333; f = 8540632726048333824.0000000
lambda =    0.11111; f = 948959191565896704.0000000
lambda =   0.037037; f = 105439910101570944.0000000
lambda =   0.012346; f = 11715545542701634.0000000
lambda =  0.0041152; f = 1301727274475476.5000000
lambda =  0.0013717; f = 144636361147898.8750000
lambda = 0.00045725; f = 16070705899570.8710938
lambda = 0.00015242; f = 1785633690224.2487793
lambda = 5.0805e-05; f = 198403643415.6751099
lambda = 1.6935e-05; f =  22044815550.6284447
lambda =  5.645e-06; f =   2449412307.2215405
lambda = 1.8817e-06; f =    272152638.4815193
lambda = 6.2723e-07; f =     30237350.2567819
lambda = 2.0908e-07; f =      3358691.3676203
lambda = 6.9692e-08; f =       372446.1873034
lambda = 2.3231e-08; f =        40730.8180079
lambda = 7.7435e-09; f =         3903.1145973
lambda = 2.5812e-09; f =         -179.0479146

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     10105698.6150643
lambda = -2.0908e-07; f =      1121588.8863450
lambda = -6.9692e-08; f =       123797.3641993
lambda = -2.3231e-08; f =        13075.9055488
lambda = -7.7435e-09; f =          821.5067524
lambda = -2.5812e-09; f =         -524.0979478
Norm of dx 1.0127e+10
Predicted improvement:        0.008473182
lambda =          1; f =         -681.2580568
lambda =    0.33333; f =         -684.1802600
lambda =    0.11111; f =         -684.5024129
lambda =   0.037037; f =         -684.5373702
lambda =   0.012346; f =         -684.5409753
lambda =  0.0041152; f =         -684.5412829
lambda =  0.0013717; f =         -684.5412861
lambda =  0.0026518; f =         -684.5412908
Norm of dx   0.060539
Predicted improvement:        0.000012468
lambda =          1; f =         -684.5413033
Norm of dx 4.5319e-05
Done for param e_a =   0.1024; f = -684.5413
Predicted improvement:        0.000012453
lambda =          1; f =         -684.5413157
Norm of dx 2.6955e-05
Done for param bet =   0.9096; f = -684.5413
Predicted improvement:        0.000022027
lambda =          1; f =         -684.5413377
Norm of dx 6.6254e-06
Done for param delt =   0.0999; f = -684.5413
Predicted improvement:        0.000020289
lambda =          1; f =         -684.5413580
Norm of dx 0.00036732
Done for param sig =   2.1111; f = -684.5414
Predicted improvement:        0.000010389
lambda =          1; f =         -684.5413684
Norm of dx  0.0016532
Done for param phi2 =   5.5535; f = -684.5414
Predicted improvement:        0.000080225
lambda =          1; f =         -684.5414486
Norm of dx 0.00019044
Done for param hf =   0.6759; f = -684.5414
Sequence of univariate steps!!
Actual dxnorm 0.0017467
FVAL          -684.5414
Improvement   0.00017956
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  2.936096e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.24715 s.
 
Iteration 28
Correct for low angle: 2.13191e-11
Predicted improvement: 79968376.599348500
lambda =          1; f = 11289692468973002.0000000
lambda =    0.33333; f = 1254410266395395.0000000
lambda =    0.11111; f = 139378915842994.1562500
lambda =   0.037037; f = 15486545322579.3437500
lambda =   0.012346; f = 1720726963594.9926758
lambda =  0.0041152; f = 191191786283.9777832
lambda =  0.0013717; f =  21243498552.5767593
lambda = 0.00045725; f =   2360377239.0287099
lambda = 0.00015242; f =    262259904.5407265
lambda = 5.0805e-05; f =     29138174.8996987
lambda = 1.6935e-05; f =      3236566.7069451
lambda =  5.645e-06; f =       358878.9726494
lambda = 1.8817e-06; f =        39224.6539879
lambda = 6.2723e-07; f =         3736.1231825
lambda = 2.0908e-07; f =         -197.5477850
lambda = 6.9692e-08; f =         -631.4559630
lambda = 2.3231e-08; f =         -678.7685975
lambda = 7.7435e-09; f =         -683.9294922
lambda = 2.5812e-09; f =         -684.4821315

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =    243056838.3867705
lambda = -2.0908e-07; f =     26983667.1503758
lambda = -6.9692e-08; f =      2990236.5246799
lambda = -2.3231e-08; f =       329199.4502351
lambda = -7.7435e-09; f =        35161.7465279
lambda = -2.5812e-09; f =         3035.2228014
Norm of dx 2.4861e+10
Predicted improvement:        0.001901845
lambda =          1; f =         -682.4319155
lambda =    0.33333; f =         -684.3078989
lambda =    0.11111; f =         -684.5157803
lambda =   0.037037; f =         -684.5386905
lambda =   0.012346; f =         -684.5411735
lambda =  0.0041152; f =         -684.5414285
lambda =  0.0013717; f =         -684.5414498
lambda = 0.00045725; f =         -684.5414499
lambda = 0.00088394; f =         -684.5414503
Norm of dx   0.045469
Predicted improvement:        0.000010589
lambda =          1; f =         -684.5414609
Norm of dx 4.1786e-05
Done for param e_a =   0.1025; f = -684.5415
Predicted improvement:        0.000034989
lambda =          1; f =         -684.5414959
Norm of dx 0.00048218
Done for param sig =   2.1106; f = -684.5415
Predicted improvement:        0.000012681
lambda =          1; f =         -684.5415086
Norm of dx 0.00033721
Done for param phi1 =   1.4074; f = -684.5415
Predicted improvement:        0.000061109
lambda =          1; f =         -684.5415697
Norm of dx 0.00016611
Done for param hf =   0.6761; f = -684.5416
Predicted improvement:        0.000026231
lambda =          1; f =         -684.5415959
Norm of dx 0.00062816
Done for param rhov =   0.2216; f = -684.5416
Sequence of univariate steps!!
Actual dxnorm 0.0008924
FVAL          -684.5416
Improvement   0.00014728
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  9.000560e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.46429 s.
 
Iteration 29
Correct for low angle: 2.54354e-11
Predicted improvement: 2690259778.563064575
lambda =          1; f = 272790079403772998582272.0000000
lambda =    0.33333; f = 30310008821903064563712.0000000
lambda =    0.11111; f = 3367778757743101870080.0000000
lambda =   0.037037; f = 374197639667191119872.0000000
lambda =   0.012346; f = 41577515491229343744.0000000
lambda =  0.0041152; f = 4619723934354103296.0000000
lambda =  0.0013717; f = 513302656334071104.0000000
lambda = 0.00045725; f = 57033627468693936.0000000
lambda = 0.00015242; f = 6337069381120199.0000000
lambda = 5.0805e-05; f = 704118707582877.0000000
lambda = 1.6935e-05; f = 78235374439390.7812500
lambda =  5.645e-06; f = 8692806877001.4140625
lambda = 1.8817e-06; f = 965863261994.5101318
lambda = 6.2723e-07; f = 107316750228.0850525
lambda = 2.0908e-07; f =  11923619628.4479733
lambda = 6.9692e-08; f =   1324691649.4933836
lambda = 2.3231e-08; f =    147135903.1843834
lambda = 7.7435e-09; f =     16330681.7340624
lambda = 2.5812e-09; f =      1808203.2762234

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =      2293584.3373192
lambda = -2.0908e-07; f =       254128.8917151
lambda = -6.9692e-08; f =        27593.8065869
lambda = -2.3231e-08; f =         2446.8249841
lambda = -7.7435e-09; f =         -339.4424378
lambda = -2.5812e-09; f =         -646.6733063
Norm of dx  5.223e+11
Predicted improvement:        0.000115945
lambda =          1; f =         -684.5410037
lambda =    0.33333; f =         -684.5415816
lambda =    0.11111; f =         -684.5416115
Norm of dx  0.0040933
Predicted improvement:        0.000013265
lambda =          1; f =         -684.5416247
Norm of dx 0.00029682
Done for param sig =   2.1105; f = -684.5416
Predicted improvement:        0.000021612
lambda =          1; f =         -684.5416464
Norm of dx 9.8709e-05
Done for param hf =   0.6762; f = -684.5416
Predicted improvement:        0.000010263
lambda =          1; f =         -684.5416566
Norm of dx 0.00037208
Done for param rhog =   0.6670; f = -684.5417
Sequence of univariate steps!!
Actual dxnorm 0.00056312
FVAL          -684.5417
Improvement   6.0752e-05
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  3.028276e-25.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.21589 s.
 
Iteration 30
Near-singular H problem.
Correct for low angle: 1.13386e-20
Predicted improvement: 11487022013.578479767
lambda =          1; f = 20512307351006961664.0000000
lambda =    0.33333; f = 2279145260980335872.0000000
lambda =    0.11111; f = 253238362250261696.0000000
lambda =   0.037037; f = 28137595778621960.0000000
lambda =   0.012346; f = 3126399521970034.0000000
lambda =  0.0041152; f = 347377721666946.6250000
lambda =  0.0013717; f = 38597523630460.1484375
lambda = 0.00045725; f = 4288613403247.2026367
lambda = 0.00015242; f = 476512488800.2033691
lambda = 5.0805e-05; f =  52945794498.3136826
lambda = 1.6935e-05; f =   5882853121.4367065
lambda =  5.645e-06; f =    653645631.7836039
lambda = 1.8817e-06; f =     72625317.0072978
lambda = 6.2723e-07; f =      8068417.4642396
lambda = 2.0908e-07; f =       895732.8950227
lambda = 6.9692e-08; f =        98868.2297036
lambda = 2.3231e-08; f =        10360.9451976
lambda = 7.7435e-09; f =          537.7893191
lambda = 2.5812e-09; f =         -550.0140965

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =     40301109.3491962
lambda = -2.0908e-07; f =      4477026.6623555
lambda = -6.9692e-08; f =       496756.7297074
lambda = -2.3231e-08; f =        54561.5364228
lambda = -7.7435e-09; f =         5446.0473613
lambda = -2.5812e-09; f =           -5.7014189
Norm of dx 1.1089e+10
Predicted improvement:        0.000022768
lambda =          1; f =         -684.5416796
Norm of dx 0.00056656
Predicted improvement:        0.000010847
lambda =          1; f =         -684.5416905
Norm of dx 4.2306e-05
Done for param e_a =   0.1025; f = -684.5417
Predicted improvement:        0.000014735
lambda =          1; f =         -684.5417052
Norm of dx  0.0019693
Done for param phi2 =   5.5555; f = -684.5417
Sequence of univariate steps!!
Actual dxnorm 0.0020496
FVAL          -684.5417
Improvement   4.8561e-05
Ftol          1e-05
Htol          1e-05
[Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND =  6.553733e-26.] 
[> In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('mr_hessian', 'C:\dynare\6.4\matlab\optimization\mr_hessian.m', 258)" style="font-weight:bold">mr_hessian</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\mr_hessian.m',258,0)">line 258</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('newrat', 'C:\dynare\6.4\matlab\optimization\newrat.m', 275)" style="font-weight:bold">newrat</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\newrat.m',275,0)">line 275</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_minimize_objective', 'C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m', 338)" style="font-weight:bold">dynare_minimize_objective</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\optimization\dynare_minimize_objective.m',338,0)">line 338</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation_1', 'C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m', 244)" style="font-weight:bold">dynare_estimation_1</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation_1.m',244,0)">line 244</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare_estimation', 'C:\dynare\6.4\matlab\estimation\dynare_estimation.m', 105)" style="font-weight:bold">dynare_estimation</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\estimation\dynare_estimation.m',105,0)">line 105</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('salvador.driver', 'E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m', 609)" style="font-weight:bold">salvador.driver</a> (<a href="matlab: opentoline('E:\My New Papers & Books\Paper_2 DSGE dollarized economies\DEF_FOLDER\Din_Mat_Estimation\+salvador\driver.m',609,0)">line 609</a>)
In <a href="matlab:matlab.lang.internal.introspective.errorDocCallback('dynare', 'C:\dynare\6.4\matlab\dynare.m', 308)" style="font-weight:bold">dynare</a> (<a href="matlab: opentoline('C:\dynare\6.4\matlab\dynare.m',308,0)">line 308</a>)
] 
Elapsed time for iteration 0.25558 s.
 
Iteration 31
Correct for low angle: 1.7681e-12
Predicted improvement: 558453387.349976182
lambda =          1; f = 11820391000091037532160.0000000
lambda =    0.33333; f = 1313376777634193604608.0000000
lambda =    0.11111; f = 145930753019232960512.0000000
lambda =   0.037037; f = 16214528096170418176.0000000
lambda =   0.012346; f = 1801614227215263488.0000000
lambda =  0.0041152; f = 200179356681953152.0000000
lambda =  0.0013717; f = 22242150109931960.0000000
lambda = 0.00045725; f = 2471349801378505.5000000
lambda = 0.00015242; f = 274594352096271.2187500
lambda = 5.0805e-05; f = 30510460139480.3593750
lambda = 1.6935e-05; f = 3390043317285.7109375
lambda =  5.645e-06; f = 376668876191.4505615
lambda = 1.8817e-06; f =  41851229119.7300491
lambda = 6.2723e-07; f =   4649846757.8524170
lambda = 2.0908e-07; f =    516552636.4787995
lambda = 6.9692e-08; f =     57362003.3308163
lambda = 2.3231e-08; f =      6362244.9441137
lambda = 7.7435e-09; f =       702746.1244930
lambda = 2.5812e-09; f =        76293.2520088

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =        91127.4980352
lambda = -2.0908e-07; f =         9500.0967775
lambda = -6.9692e-08; f =          442.0100626
lambda = -2.3231e-08; f =         -560.6451624
lambda = -7.7435e-09; f =         -671.0417155
lambda = -2.5812e-09; f =         -683.0923382
Norm of dx 1.0872e+11
Predicted improvement:        0.000000553
lambda =          1; f =         -684.5417058
Norm of dx 0.00033994
Sequence of univariate steps!!
Try diagonal Hessian
Predicted improvement:        0.000075346
lambda =          1; f =         -684.5396448
lambda =    0.33333; f =         -684.5415100
lambda =    0.11111; f =         -684.5416951
lambda =   0.037037; f =         -684.5417083
Norm of dx 0.00022785
Try gradient direction
Predicted improvement:        0.000211074
lambda =          1; f =         -684.5255246
lambda =    0.33333; f =         -684.5399070
lambda =    0.11111; f =         -684.5415071
lambda =   0.037037; f =         -684.5416856
lambda =   0.012346; f =         -684.5417056
lambda =  0.0041152; f =         -684.5417079
lambda =  0.0013717; f =         -684.5417082
lambda = 0.00045725; f =         -684.5417083
lambda = 0.00015242; f =         -684.5417083
lambda = 5.0805e-05; f =         -684.5417083
lambda = 1.6935e-05; f =         -684.5417083
lambda =  5.645e-06; f =         -684.5417083
lambda = 1.8817e-06; f =         -684.5417083
lambda = 6.2723e-07; f =         -684.5417083
lambda = 2.0908e-07; f =         -684.5417083
lambda = 6.9692e-08; f =         -684.5417083
lambda = 2.3231e-08; f =         -684.5417083
lambda = 7.7435e-09; f =         -684.5417083
lambda = 2.5812e-09; f =         -684.5417083

lambda =

  -6.2723e-07

lambda = -6.2723e-07; f =         -684.5417083
Norm of dx 0.00020546
No further improvement is possible!
Actual dxnorm 0.00034005
FVAL          -684.5417
Improvement   3.0641e-06
Ftol          1e-05
Htol          1e-05
Gradient norm  2.0546
Minimum Hessian eigenvalue 5.3186e-13
Maximum Hessian eigenvalue 3195705.5195
Estimation successful.

Final value of minus the log posterior (or likelihood):-684.541708 

RESULTS FROM POSTERIOR ESTIMATION
parameters
       prior mean     mode    s.d.  prior pstdev

alp        0.3300   0.3393  0.0200   norm 0.0200 
bet        0.9450   0.9096  0.0164   unif 0.0260 
delt       0.1000   0.0999  0.0010   norm 0.0010 
sig        2.0000   2.1100  0.0941   norm 0.1000 
phi1       1.5000   1.4078  0.1008   norm 0.1000 
phi2       5.6000   5.5558  0.5018   norm 0.5000 
psi1       1.4000   1.4000  0.5000   norm 0.5000 
hf         0.5000   0.6763  0.0416   beta 0.2000 
rhoa       0.7000   0.4713  0.0920   beta 0.2000 
rhov       0.5000   0.2215  0.1379   beta 0.2000 
rhog       0.5000   0.6670  0.0886   beta 0.2000 
rhorer     0.0000   0.5468  0.1284   unif 0.5774 
rhoyw      0.5500   0.5538  0.0743   beta 0.1000 

standard deviation of shocks
       prior mean     mode    s.d.  prior pstdev

e_a        0.0100   0.1025  0.0158   invg    Inf 
e_v        0.0100   0.1851  0.0248   invg    Inf 
e_g        0.0100   0.0406  0.0045   invg    Inf 
e_rer      0.0100   0.0436  0.0083   invg    Inf 
e_yw       0.0100   0.0101  0.0009   invg    Inf 


Log data density [Laplace approximation] is 637.284192.

Estimation::mcmc: Multiple chains mode.
Estimation::mcmc: Searching for initial values...
Estimation::mcmc: Initial values found!

Estimation::mcmc: Write details about the MCMC... Ok!
Estimation::mcmc: Details about the MCMC are available in salvador/metropolis\salvador_mh_history_0.mat


Estimation::mcmc: Number of mh files: 1 per block.
Estimation::mcmc: Total number of generated files: 2.
Estimation::mcmc: Total number of iterations: 20000.
Estimation::mcmc: Current acceptance ratio per chain:
                                                       Chain  1: 28.2%
                                                       Chain  2: 26.97%
Estimation::mcmc: Total number of MH draws per chain: 20000.
Estimation::mcmc: Total number of generated MH files: 1.
Estimation::mcmc: I'll use mh-files 1 to 1.
Estimation::mcmc: In MH-file number 1 I'll start at line 10001.
Estimation::mcmc: Finally I keep 10000 draws per chain.

marginal density: I'm computing the posterior mean and covariance...  Done!
marginal density: I'm computing the posterior log marginal density (modified harmonic mean)... Done!


ESTIMATION RESULTS

Log data density (Modified Harmonic Mean) is 636.943991.
parameters
         prior mean   post. mean        90% HPD interval    prior       pstdev

alp           0.330       0.3357      0.3066      0.3676     norm       0.0200
bet           0.945       0.9190      0.9002      0.9364     unif       0.0260
delt          0.100       0.0999      0.0983      0.1014     norm       0.0010
sig           2.000       2.1172      1.9748      2.2686     norm       0.1000
phi1          1.500       1.4260      1.2677      1.5910     norm       0.1000
phi2          5.600       5.5071      4.6360      6.3093     norm       0.5000
psi1          1.400       1.4307      0.6160      2.2375     norm       0.5000
hf            0.500       0.6809      0.6158      0.7456     beta       0.2000
rhoa          0.700       0.4832      0.3217      0.6371     beta       0.2000
rhov          0.500       0.2647      0.0529      0.4521     beta       0.2000
rhog          0.500       0.6438      0.5157      0.7914     beta       0.2000
rhorer        0.000       0.5112      0.3060      0.7167     unif       0.5774
rhoyw         0.550       0.5556      0.4399      0.6754     beta       0.1000

standard deviation of shocks
         prior mean   post. mean        90% HPD interval    prior       pstdev

e_a           0.010       0.1125      0.0835      0.1406     invg          Inf
e_v           0.010       0.2057      0.1577      0.2497     invg          Inf
e_g           0.010       0.0440      0.0363      0.0525     invg          Inf
e_rer         0.010       0.0496      0.0348      0.0645     invg          Inf
e_yw          0.010       0.0103      0.0087      0.0117     invg          Inf
Estimation::mcmc: Posterior (dsge) IRFs...
Estimation::mcmc: Posterior IRFs, done!
Estimation::compute_moments_varendo: I'm computing endogenous moments (this may take a while)... 


Posterior mean variance decomposition (in percent)
          e_a     e_v     e_g   e_rer    e_yw
y       86.09    3.61    9.34    0.92    0.04
x       77.97   21.47    0.50    0.05    0.00
c       85.57   12.90    1.42    0.10    0.01
w       99.04    0.74    0.20    0.02    0.00
R        8.07    0.35   84.77    6.47    0.33
k       80.30   18.93    0.71    0.06    0.00
d        5.25    0.20   85.79    8.36    0.39
r       70.35   22.53    6.48    0.61    0.03
l       97.10    0.72    1.97    0.19    0.01
la      76.96   22.26    0.71    0.07    0.00
tb      33.95    1.38    3.58   58.28    2.81
a      100.00    0.00   -0.00   -0.00   -0.00
v        0.00  100.00    0.00    0.00    0.00
g        0.00    0.00  100.00    0.00    0.00
rer      0.00    0.00    0.00  100.00    0.00
yw       0.00    0.00    0.00    0.00  100.00


Done!

Estimation::mcmc: Smoothed variables
Estimation::mcmc: Smoothed variables, done!
Estimation::mcmc: Smoothed shocks
Estimation::mcmc: Smoothed shocks, done!
Estimation::mcmc: Trend_coefficients
Estimation::mcmc: Trend_coefficients, done!
Estimation::mcmc: Smoothed constant
Estimation::mcmc: Smoothed constant, done!
Estimation::mcmc: Smoothed trend
Estimation::mcmc: Smoothed trend, done!
Estimation::mcmc: Updated Variables
[Warning: Exported image displays axes toolbar. To remove axes toolbar from image, export again.] 
[Warning: Exported image displays axes toolbar. To remove axes toolbar from image, export again.] 
Estimation::mcmc: Updated Variables, done!
Total computing time : 0h07m31s
Note: warning(s) encountered in MATLAB/Octave code
